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Browse AI Concepts & Ontology Classes

Explore 1255 artificial intelligence concepts, comprising 813 evidence-curated algorithms, architectures, and model families alongside 442 classes projected from the Artificial Intelligence Ontology (AIO).

Showing 1255 of 1255

Concept	Origin	Kind / Branch	Identifier	Evidence / Status
A-star beam search for sequence decoding aka A* beam search for sequence decoding A sequence-decoding beam framework that ranks active hypotheses by accumulated score plus an optimistic future-score heuristic, uses shorter…	Curated	Algorithms	`AIMech:SequenceAStarBeamSearch`	2 claims 2 sources
A-star search aka A* search A heuristic graph-search method that selects an open node using the sum of its best known path cost from the start and an estimated remainin…	Curated	Algorithms	`AIMech:AStarSearch`	1 claim 1 source
ABRA-s progressive betweenness approximation aka ABRA-s, ABRA static progressive betweenness approximation A progressive sampling algorithm for static-graph betweenness that averages fractions of shortest paths through each node over uniformly sam…	Curated	Algorithms	`AIMech:ABRASProgressiveBetweenness`	6 claims 1 source
ABRA-s-fix fixed-sample betweenness approximation aka ABRA-s-fix, ABRA fixed-sample betweenness approximation A fixed-sample static-graph betweenness algorithm that averages shortest-path fractions over a user-specified number of uniform endpoint pai…	Curated	Algorithms	`AIMech:ABRASFixedSampleBetweenness`	6 claims 1 source
Absolute threshold pruning for sequence beams A sequence-beam pruning procedure that first applies the beam-size cap, then discards candidates whose score is at least a specified positiv…	Curated	Algorithms	`AIMech:AbsoluteThresholdBeamPruning`	2 claims 2 sources
AbstractRNNCell A layer representing an RNN cell that is the base class for implementing RNN cells with custom behavior.	AIO	Layer	`AIO:AbstractRNNCell`	Imported
Accelerated graph degree linkage aka AGDL An approximate graph degree linkage algorithm that selects merges from maintained cluster-neighbor sets and updates those sets locally inste…	Curated	Algorithms	`AIMech:AcceleratedGraphDegreeLinkage`	1 claim 1 source
Accumulating Sarsa(lambda) An episodic tabular on-policy control algorithm that propagates each selected-next-action temporal-difference error through accumulating sta…	Curated	Algorithms	`AIMech:AccumulatingSarsaLambda`	6 claims 8 sources
Activation Layer A layer that applies an activation function to an output.	AIO	Layer	`AIO:ActivationLayer`	Imported
Activation-Value Gaussian Pooling aka Diff-Gauss pooling A parameterized neural pooling unit that averages a group of transformed activations using normalized Gaussian-kernel weights determined by…	Curated	Mathematical Methods	`AIMech:ActivationValueGaussianPooling`	5 claims 1 source
Active CMA covariance update A matrix-valued covariance-update component from the original 2006 active CMA construction that combines retained search covariance and an e…	Curated	Mathematical Methods	`AIMech:ActiveCMACovarianceUpdate`	6 claims 1 source
Active Learning aka Query Learning A machine learning task focused on methods that interactively query a user or another information source to label new data points with the d…	AIO	MachineLearningTask	`AIO:ActiveLearning`	Imported
Activity Bias A use and interpretation bias occurring when systems/platforms get training data from their most active users rather than less active or ina…	AIO	Bias	`AIO:ActivityBias`	Imported
ActivityRegularization Layer A regularization layer that applies an update to the cost function based on input activity.	AIO	Layer	`AIO:ActivityRegularizationLayer`	Imported
AdaBoost aka Adaptive boosting Boosting that reweights training observations according to prior prediction errors.	Curated	Algorithms	`AIMech:AdaBoost`	1 claim 1 source
Adadelta An adaptive gradient optimization method that rescales gradients using exponentially weighted squared-gradient and squared-update histories.	Curated	Algorithms	`AIMech:Adadelta`	1 claim 1 source
Adafactor An adaptive gradient optimization method that approximates matrix-valued second-moment statistics using row and column factors.	Curated	Algorithms	`AIMech:Adafactor`	1 claim 2 sources
Adagrad An adaptive gradient optimization method that scales each coordinate's update using accumulated squared gradients.	Curated	Algorithms	`AIMech:Adagrad`	1 claim 1 source
Adam aka Adaptive moment estimation Stochastic gradient optimization using bias-corrected exponential estimates of first and second gradient moments to scale parameter updates.	Curated	Algorithms	`AIMech:Adam`	2 claims 2 sources
AdaMax An Adam-family optimizer using an exponentially weighted infinity-norm gradient scale instead of a second raw moment denominator.	Curated	Algorithms	`AIMech:AdaMax`	1 claim 1 source
AdaMixUp aka Adaptive MixUp An adaptive interpolation-training procedure that learns example-dependent mixing-coefficient regions with a policy network and trains a cla…	Curated	Algorithms	`AIMech:AdaMixUp`	2 claims 2 sources
AdamNC An Adam-family optimization method that uses time-dependent first- and second-moment decay schedules.	Curated	Algorithms	`AIMech:AdamNC`	1 claim 1 source
AdamW An Adam optimization variant that applies weight decay directly to parameters separately from gradient moment estimation.	Curated	Algorithms	`AIMech:AdamW`	1 claim 1 source
Adaptation sampling An online optimizer-hyperparameter controller that compares sample quality under a current and a hypothetical setting, using either fresh ev…	Curated	Algorithms	`AIMech:AdaptationSampling`	6 claims 3 sources
Adaptive Alternating Minimization aka AAM (adaptive alternating minimization) A two-coordinate minimization procedure that performs one exact alternating sweep over a newly supplied pair of feasible sets at each iterat…	Curated	Algorithms	`AIMech:AdaptiveAlternatingMinimization`	4 claims 1 source
Adaptive Deconvolutional Network An unsupervised hierarchical image-representation architecture that alternates convolutional sparse synthesis with spatial and cross-map poo…	Curated	Architectures	`AIMech:AdaptiveDeconvolutionalNetwork`	5 claims 2 sources
Adaptive Metropolis aka Adaptive Metropolis algorithm A history-adaptive random-walk Metropolis sampler whose Gaussian proposal covariance is estimated from the accumulated retained states, incl…	Curated	Algorithms	`AIMech:AdaptiveMetropolis`	1 claim 2 sources
Adaptive parallel tempering aka Adaptive parallel tempering algorithm A parallel-tempering algorithm that adapts temperature gaps and within-replica random-walk proposal parameters through projected stochastic…	Curated	Algorithms	`AIMech:AdaptiveParallelTempering`	1 claim 1 source
Adaptive rejection sampling aka ARS The Gilks–Wild univariate rejection sampler that uses tangents to a concave log density as a piecewise-linear upper hull and chords as a low…	Curated	Algorithms	`AIMech:AdaptiveRejectionSampling`	1 claim 1 source
Adaptive scaling Metropolis aka ASM A random-walk Metropolis algorithm that adapts its proposal scale through stochastic approximation driven by the proposal acceptance probabi…	Curated	Algorithms	`AIMech:AdaptiveScalingMetropolis`	1 claim 1 source
Adaptive scaling within adaptive Metropolis aka ASWAM An adaptive Metropolis algorithm that combines acceptance-rate-driven scalar proposal scaling with recursive mean and covariance-shape adapt…	Curated	Algorithms	`AIMech:AdaptiveScalingWithinAdaptiveMetropolis`	1 claim 1 source
AdaptiveAvgPool1D Layer aka AdaptiveAvgPool1D A pooling layer that applies a 1D adaptive average pooling over an input signal composed of several input planes.	AIO	Layer	`AIO:AdaptiveAvgPool1DLayer`	Imported
AdaptiveAvgPool2D Layer aka AdaptiveAvgPool2D A pooling layer that applies a 2D adaptive average pooling over an input signal composed of several input planes.	AIO	Layer	`AIO:AdaptiveAvgPool2DLayer`	Imported
AdaptiveAvgPool3D Layer aka AdaptiveAvgPool3D A pooling layer that applies a 3D adaptive average pooling over an input signal composed of several input planes.	AIO	Layer	`AIO:AdaptiveAvgPool3DLayer`	Imported
AdaptiveMaxPool1D Layer aka AdaptiveMaxPool1D A pooling layer that applies a 1D adaptive max pooling over an input signal composed of several input planes.	AIO	Layer	`AIO:AdaptiveMaxPool1DLayer`	Imported
AdaptiveMaxPool2D Layer aka AdaptiveMaxPool2D A pooling layer that applies a 2D adaptive max pooling over an input signal composed of several input planes.	AIO	Layer	`AIO:AdaptiveMaxPool2DLayer`	Imported
AdaptiveMaxPool3D Layer aka AdaptiveMaxPool3D A pooling layer that applies a 3D adaptive max pooling over an input signal composed of several input planes.	AIO	Layer	`AIO:AdaptiveMaxPool3DLayer`	Imported
Add Layer A merging layer that adds a list of inputs taking as input a list of tensors all of the same shape.	AIO	Layer	`AIO:AddLayer`	Imported
Addition Layer A layer that adds inputs from one or more other layers to cells or neurons of a target layer.	AIO	Layer	`AIO:AdditionLayer`	Imported
AdditiveAttention Layer An attention layer that implements additive attention also known as Bahdanau-style attention.	AIO	Layer	`AIO:AdditiveAttentionLayer`	Imported
Admixture of Poisson Markov random fields aka Admixture of Poisson MRFs, APM A probabilistic topic-model family that draws each document from a proper Poisson-MRF base distribution whose canonical unary and interactio…	Curated	Model Families	`AIMech:AdmixtureOfPoissonMarkovRandomFields`	2 claims 6 sources
Adversarial debiasing (Zhang et al.) aka Zhang projected-gradient adversarial debiasing An adversarial learning algorithm that trains a task predictor alongside a protected-attribute adversary, modifying the predictor gradient w…	Curated	Algorithms	`AIMech:ZhangAdversarialDebiasing`	2 claims 2 sources
AlphaDropout Layer A regularization layer that applies Alpha Dropout to the input keeping mean and variance of inputs to ensure self-normalizing property.	AIO	Layer	`AIO:AlphaDropoutLayer`	Imported
Alternating Expectation Conditional Maximization aka AECM, AECM Algorithm A likelihood-optimization framework that alternates cycles of expectation and constrained maximization, permitting the admissible data augme…	Curated	Algorithms	`AIMech:AlternatingExpectationConditionalMaximization`	4 claims 1 source
Alternating Kullback-Leibler Minimization aka Alternating I-Divergence Minimization, Alternating Information Projection A paired-distribution optimization procedure that alternately minimizes Kullback-Leibler divergence in its first and second arguments over s…	Curated	Algorithms	`AIMech:AlternatingKullbackLeiblerMinimization`	4 claims 1 source
Amortized Stein variational gradient descent aka Amortized SVGD A differentiable stochastic-sampler training procedure that repeatedly generates a minibatch, computes kernelized Stein target-score directi…	Curated	Algorithms	`AIMech:AmortizedSteinVariationalGradientDescent`	6 claims 2 sources
Amplification Bias A processing bias arising when the distribution over prediction outputs is skewed compared to the prior distribution of the prediction targe…	AIO	Bias	`AIO:AmplificationBias`	Imported
AMSGrad An Adam variant that normalizes first-moment updates with the coordinatewise historical maximum of second-moment estimates.	Curated	Algorithms	`AIMech:AMSGrad`	1 claim 1 source
Analytic moment-based Gaussian-process filtering aka Gaussian-process assumed-density filtering, GP-ADF A Gaussian assumed-density filtering algorithm that uses trained squared-exponential Gaussian-process transition and measurement models, ana…	Curated	Algorithms	`AIMech:AnalyticMomentBasedGaussianProcessFiltering`	5 claims 2 sources
Ancestral Gumbel-Top-k sampling An exact without-replacement sampler for finite discrete Bayesian-network configurations that propagates conditional Gumbel subtree maxima t…	Curated	Algorithms	`AIMech:AncestralGumbelTopKSampling`	3 claims 1 source
Anchoring Bias An individual bias characterized by the influence of a reference point or anchor on decisions leading to insufficient adjustment from that a…	AIO	Bias	`AIO:AnchoringBias`	Imported
AND/OR abstraction sampling aka Unrestricted AND/OR abstraction sampling An importance-sampling algorithm for partition functions of discrete graphical models that samples representatives in a pseudo-tree-guided A…	Curated	Algorithms	`AIMech:ANDORAbstractionSampling`	5 claims 2 sources
Annealed importance sampling aka AIS A Monte Carlo estimation algorithm that draws from a tractable base distribution, applies Markov transitions invariant for a prescribed sequ…	Curated	Algorithms	`AIMech:AnnealedImportanceSampling`	6 claims 1 source
Annotator Reporting Bias An individual bias occurring when users rely on automation as a heuristic replacement for their own information seeking and processing.	AIO	Bias	`AIO:AnnotatorReportingBias`	Imported
Ant colony optimization aka ACO, Ant colony optimization metaheuristic A metaheuristic framework for optimization in which artificial ants construct solutions using local information and communicate indirectly t…	Curated	Algorithms	`AIMech:AntColonyOptimization`	1 claim 1 source
Ant Colony System aka ACS An ant-colony optimization algorithm that combines a greedy-or-proportional construction rule, local pheromone updates during construction,…	Curated	Algorithms	`AIMech:AntColonySystem`	1 claim 2 sources
Ant System A constructive combinatorial optimization method in which artificial ants sample solution components using shared pheromone trails and probl…	Curated	Algorithms	`AIMech:AntSystem`	1 claim 1 source
Ant-based telephone routing A distributed telephone-routing algorithm that adapts neighbor-choice probabilities using mobile ant agents. Ants sample moves from destinat…	Curated	Algorithms	`AIMech:AntBasedTelephoneRouting`	5 claims 1 source
Ant-Q A family of cooperative ant-based optimization algorithms that learns shared edge desirabilities using Q-learning-inspired next-state estima…	Curated	Algorithms	`AIMech:AntQ`	1 claim 2 sources
AntNet A distributed adaptive routing algorithm in which forward agents sample network paths and backward agents use the measured trip times to upd…	Curated	Algorithms	`AIMech:AntNet`	1 claim 1 source
Apriori Frequent-itemset mining using breadth-first candidate enumeration and support-based pruning.	Curated	Algorithms	`AIMech:Apriori`	1 claim 1 source
Artificial Neural Network aka ANN, NN A network based on a collection of connected units called artificial neurons modeled after biological neurons.	AIO	Network	`AIO:ArtificialNeuralNetwork`	Imported
Association Rule Learning A supervised learning focused on a rule-based approach for discovering interesting relations between variables in large databases.	AIO	MachineLearningTask	`AIO:AssociationRuleLearning`	Imported
Asynchronous Successive Halving aka ASHA, Asynchronous Successive Halving Algorithm An asynchronous resource-allocation algorithm that promotes promising completed hyperparameter trials through increasing resource levels as…	Curated	Algorithms	`AIMech:AsynchronousSuccessiveHalving`	1 claim 2 sources
Attention Layer A layer that implements dot-product attention also known as Luong-style attention.	AIO	Layer	`AIO:AttentionLayer`	Imported
Attention-Based Configurable Convolutional Neural Network aka ABC-CNN A visual-question-answering architecture that derives a convolution kernel from an encoded question to compute normalized spatial attention,…	Curated	Architectures	`AIMech:AttentionBasedConfigurableConvolutionalNeuralNetwork`	6 claims 1 source
Attention-Based Convolutional Neural Network aka ABCNN A sentence-pair neural architecture that uses cross-sentence distance affinities to add attention feature channels before convolution, rewei…	Curated	Architectures	`AIMech:AttentionBasedConvolutionalNeuralNetwork`	6 claims 1 source
Attention-based Dropout Layer aka ADL A training-time convolutional feature-map layer that stochastically applies either a thresholded spatial drop mask or sigmoid importance wei…	Curated	Layers & Modules	`AIMech:AttentionBasedDropoutLayer`	1 claim 1 source
Attentive Pooling Network aka Attentive Pooling Networks A neural sentence-pair architecture that learns bilinear segment interactions, derives attention by row and column maxima followed by separa…	Curated	Architectures	`AIMech:AttentivePoolingNetwork`	6 claims 1 source
Author-persona-topic model aka APT A probabilistic topic-model family in which each author has a mixture of personas, each persona has a topic distribution, and one persona sh…	Curated	Model Families	`AIMech:AuthorPersonaTopicModel`	3 claims 1 source
Author-recipient-topic model aka ART A generative message model with a topic distribution for each ordered sender-recipient pair, in which each word selects a recipient uniforml…	Curated	Model Families	`AIMech:AuthorRecipientTopicModel`	2 claims 2 sources
Author-topic model A generative document model in which each author has a shared topic-proportion distribution and each word is produced by uniformly selecting…	Curated	Model Families	`AIMech:AuthorTopicModel`	2 claims 1 source
Auto Encoder Network aka AE An unsupervised pretrained network that learns efficient codings of unlabeled data by training to ignore insignificant data and regenerate i…	AIO	Network	`AIO:AutoEncoderNetwork`	Imported
Auto-binomial Markov random field aka Auto-binomial model, Auto-binomial scheme A finite pairwise Markov-field model for bounded site counts whose full conditionals are binomial with fixed trial counts and log odds linea…	Curated	Model Families	`AIMech:AutoBinomialMarkovRandomField`	1 claim 1 source
Auto-exponential Markov random field aka Auto-exponential model, Auto-exponential scheme A finite pairwise Markov-field model for nonnegative continuous site values with exponential full conditionals whose rates are positive base…	Curated	Model Families	`AIMech:AutoExponentialMarkovRandomField`	1 claim 1 source
Auto-normal Markov random field aka Auto-normal model, Auto-normal scheme… A proper finite Gaussian Markov-field model specified by linear full-conditional means and positive, value-independent site conditional vari…	Curated	Model Families	`AIMech:AutoNormalMarkovRandomField`	1 claim 2 sources
Auto-Poisson Markov random field aka Auto-Poisson model, Auto-Poisson scheme A finite pairwise Markov-field model for unbounded nonnegative integer counts whose full conditionals are Poisson with log means linear in n…	Curated	Model Families	`AIMech:AutoPoissonMarkovRandomField`	1 claim 1 source
Auto-Walksat A preprocessing-and-run algorithm that estimates a fixed noise setting for a stochastic SAT solver by probing a terminal-score mean-to-stand…	Curated	Algorithms	`AIMech:AutoWalksat`	5 claims 2 sources
AutoAugment An automated augmentation-policy search procedure that trains a controller to propose image-transform subpolicies and rewards those proposal…	Curated	Algorithms	`AIMech:AutoAugment`	1 claim 1 source
Automation Complacency Bias aka Automation Complaceny An individual bias characterized by over-reliance on automated systems leading to attenuated human skills.	AIO	Bias	`AIO:AutomationComplacencyBias`	Imported
Autoregressive Conditional Heteroskedasticity aka ARCH A model that describes the variance of the current error term as a function of the previous periods' error terms, capturing volatility clust…	AIO	Model	`AIO:AutoregressiveConditionalHeteroskedasticity`	Imported
Autoregressive conditional restricted Boltzmann machine aka Autoregressive CRBM A neural sequence architecture that models each current vector with a conditional RBM whose visible and hidden biases are affine functions o…	Curated	Architectures	`AIMech:AutoregressiveConditionalRestrictedBoltzmannMachine`	1 claim 2 sources
Autoregressive Distributed Lag aka ARDL A model that includes lagged values of both the dependent variable and one or more independent variables, capturing dynamic relationships ov…	AIO	Model	`AIO:AutoregressiveDistributedLag`	Imported
Autoregressive Integrated Moving Average aka ARIMA A model which combines autoregression (AR), differencing (I), and moving average (MA) components. Used for analyzing and forecasting time se…	AIO	Model	`AIO:AutoregressiveIntegratedMovingAverage`	Imported
Autoregressive Language Model aka generative language model, sequence-to-sequence model A language model that generates text sequentially predicting one token at a time based on the previously generated tokens excelling at natur…	AIO	Model	`AIO:AutoregressiveLanguageModel`	Imported
Autoregressive Moving Average aka ARMA A model that combines autoregressive (AR) and moving average (MA) components to represent time series data, suitable for stationary series w…	AIO	Model	`AIO:AutoregressiveMovingAverage`	Imported
Availability Heuristic Bias aka Availability Bias, Availability Heuristic An individual bias characterized by a mental shortcut where easily recalled information is overweighted in judgment and decision-making.	AIO	Bias	`AIO:AvailabilityHeuristicBias`	Imported
Average Layer A merging layer that averages a list of inputs element-wise taking as input a list of tensors all of the same shape.	AIO	Layer	`AIO:AverageLayer`	Imported
Averaged stochastic gradient descent aka ASGD A stochastic gradient optimization method that maintains an average of parameter iterates in addition to the current iterate.	Curated	Algorithms	`AIMech:AveragedStochasticGradientDescent`	1 claim 1 source
AveragePooling1D Layer aka AvgPool1D A pooling layer that performs average pooling for temporal data.	AIO	Layer	`AIO:AveragePooling1DLayer`	Imported
AveragePooling2D Layer aka AvgPool2D A pooling layer that performs average pooling for spatial data.	AIO	Layer	`AIO:AveragePooling2DLayer`	Imported
AveragePooling3D Layer aka AvgPool3D A pooling layer that performs average pooling for 3D data (spatial or spatio-temporal).	AIO	Layer	`AIO:AveragePooling3DLayer`	Imported
AvgPool1D Layer aka AvgPool1D A pooling layer that applies a 1D average pooling over an input signal composed of several input planes.	AIO	Layer	`AIO:AvgPool1DLayer`	Imported
AvgPool2D Layer aka AvgPool2D A pooling layer that applies a 2D average pooling over an input signal composed of several input planes.	AIO	Layer	`AIO:AvgPool2DLayer`	Imported
AvgPool3D Layer aka AvgPool3D A pooling layer that applies a 3D average pooling over an input signal composed of several input planes.	AIO	Layer	`AIO:AvgPool3DLayer`	Imported
Backfed Input Layer An input layer that receives values from another layer.	AIO	Layer	`AIO:BackfedInputLayer`	Imported
Backpropagation through time aka BPTT A reverse differentiation algorithm that computes derivatives of a finite dynamic-system objective by propagating adjoints backward through…	Curated	Algorithms	`AIMech:BackpropagationThroughTime`	6 claims 1 source
Bagging aka Bootstrap aggregating Ensemble learning that aggregates predictors trained on bootstrap samples.	Curated	Algorithms	`AIMech:Bagging`	1 claim 1 source
Balanced Attention Mechanism aka BAM (balanced attention) A convolutional feature-gating component for single-image super-resolution that computes average-pooled channel attention and maximum-pooled…	Curated	Layers & Modules	`AIMech:BalancedAttentionMechanism`	6 claims 1 source
Balanced largest differencing method aka BLDM, Balanced LDM A two-way number-partitioning heuristic that first differences disjoint adjacent pairs in the sorted original list, then repeatedly differen…	Curated	Algorithms	`AIMech:BalancedLargestDifferencing`	6 claims 1 source
Ball vector machine aka BVM An approximate SVM training procedure that uses fixed-radius enclosing-ball center updates in a transformed kernel feature space, with multi…	Curated	Algorithms	`AIMech:BallVectorMachine`	7 claims 2 sources
Barber–Agakov mutual information bound aka Barber-Agakov bound, BA bound A variational lower bound on mutual information formed by adding input entropy to the expected log probability assigned by a normalized cond…	Curated	Mathematical Methods	`AIMech:BarberAgakovBound`	1 claim 2 sources
Barker acceptance rule An acceptance-probability rule for reversible Monte Carlo proposals that uses R/(1+R), where R is the target-density ratio times the reverse…	Curated	Mathematical Methods	`AIMech:BarkerAcceptanceRule`	1 claim 1 source
Barlow Twins A self-supervised representation-learning procedure that trains shared encoder and projection networks to make the cross-correlation of two…	Curated	Algorithms	`AIMech:BarlowTwins`	1 claim 3 sources
BasicILS aka BasicILS(N) A ParamILS algorithm-configuration method that compares candidate configurations using cost estimates on the same fixed number of target-alg…	Curated	Algorithms	`AIMech:BasicILS`	1 claim 1 source
Basis pursuit A signal-representation optimization principle that minimizes the L1 norm of real synthesis coefficients subject to exact reconstruction of…	Curated	Mathematical Methods	`AIMech:BasisPursuit`	7 claims 1 source
Batch reciprocal-nearest-neighbor agglomeration aka Reciprocal-neighbor batch clustering, de Rham reciprocal-neighbor clustering An agglomerative clustering procedure that alternates finding reciprocal nearest-neighbor pairs across the current clusters with merging a b…	Curated	Algorithms	`AIMech:BatchReciprocalNearestNeighborClustering`	6 claims 3 sources
BatchNorm1D Layer aka BatchNorm1D A batch normalization layer that applies Batch Normalization over a 2D or 3D input.	AIO	Layer	`AIO:BatchNorm1DLayer`	Imported
BatchNorm2D Layer aka BatchNorm2D A batch normalization layer that applies Batch Normalization over a 4D input.	AIO	Layer	`AIO:BatchNorm2DLayer`	Imported
BatchNorm3D Layer aka BatchNorm3D A batch normalization layer that applies Batch Normalization over a 5D input.	AIO	Layer	`AIO:BatchNorm3DLayer`	Imported
BatchNormalization Layer aka BatchNorm A normalization layer that normalizes its inputs applying a transformation that maintains the mean close to 0 and the standard deviation clo…	AIO	Layer	`AIO:BatchNormalizationLayer`	Imported
Bayesian Data Augmentation for Deep Models aka Bayesian Data Augmentation, Bayesian DA… Tran et al.’s supervised deep-learning procedure that treats synthetic labeled examples as latent data, repeatedly samples them from an evol…	Curated	Algorithms	`AIMech:BayesianDataAugmentation`	1 claim 1 source
Bayesian Network A network that is a probabilistic graphical model representing variables and their conditional dependencies via a directed acyclic graph.	AIO	Network	`AIO:BayesianNetwork`	Imported
Beam decoding with a monotone-score stopping certificate aka Optimal-ending beam search A layer-based sequence beam decoder that retains the best completed hypothesis seen so far and stops when the highest current prefix score c…	Curated	Algorithms	`AIMech:OptimalStoppingBeamDecoding`	2 claims 2 sources
Beam search using limited discrepancy backtracking aka BULB, Limited discrepancy beam search A memory-bounded beam search that explores heuristic-ranked slices using increasing limited-discrepancy budgets and removes backtracked slic…	Curated	Algorithms	`AIMech:BULB`	3 claims 3 sources
Beam-stack search A layer-based beam search augmented with a stack of admitted evaluation ranges so that backtracking systematically revisits successors previ…	Curated	Algorithms	`AIMech:BeamStackSearch`	2 claims 2 sources
Behavioral Bias An individual bias characterized by systematic distortions in user behavior across platforms or contexts or across users represented in diff…	AIO	Bias	`AIO:BehavioralBias`	Imported
Best-first beam search with a global frontier cap A best-first search procedure that limits the entire open frontier to a fixed number of nodes by discarding the worst-ranked frontier nodes…	Curated	Algorithms	`AIMech:GlobalFrontierBeamSearch`	3 claims 3 sources
Best-first beam search with per-length budgets The sequence-decoding beam procedure of Meister, Vieira and Cotterell that prioritizes active hypotheses by decreasing accumulated score, br…	Curated	Algorithms	`AIMech:SequenceBestFirstBeamSearch`	3 claims 3 sources
Best-first search A search strategy that repeatedly expands the open node with the best value under a specified evaluation rule, adding eligible successors to…	Curated	Algorithms	`AIMech:BestFirstSearch`	2 claims 2 sources
BI-population CMA-ES The original 2009 multistart CMA-ES algorithm that interlaces increasing-population attempts with randomized smaller population and initial-…	Curated	Algorithms	`AIMech:BIPOPCMAES`	6 claims 2 sources
Bias A systematic error introduced into sampling or testing by selecting or encouraging one outcome or answer over others.	AIO	Bias	`AIO:Bias`	Imported
Biclustering aka Block Clustering, Co-clustering… A machine learning task focused on methods that simultaneously cluster the rows and columns of a matrix to identify submatrices with coheren…	AIO	MachineLearningTask	`AIO:Biclustering`	Imported
Bidirectional Layer A recurrent layer that is a bidirectional wrapper for RNNs.	AIO	Layer	`AIO:BidirectionalLayer`	Imported
Bidirectional Transformer Language Model aka BERT, Bidirectional Transformer LM A transformer language model such as BERT that uses the transformer architecture to build deep bidirectional representations by predicting m…	AIO	Model	`AIO:BidirectionalTransformerLanguageModel`	Imported
Binary Classification A classification focused on methods that classify elements into two groups based on a classification rule.	AIO	MachineLearningTask	`AIO:BinaryClassification`	Imported
Binary Multiple Kernel Maximum Margin Clustering aka Two-Class Multiple Kernel Clustering A two-class unsupervised clustering procedure that jointly fits a nonnegative multiple-kernel combination and absolute-margin classifier usi…	Curated	Algorithms	`AIMech:BinaryMultipleKernelMaximumMarginClustering`	5 claims 1 source
BIRCH aka Balanced Iterative Reducing and Clustering using Hierarchies Clustering that compresses observations into a clustering-feature tree for subsequent grouping.	Curated	Algorithms	`AIMech:BIRCH`	1 claim 1 source
Bivariate counterfactual-fairness sensitivity analysis aka Kilbertus grid-based counterfactual-fairness sensitivity A model-based sensitivity procedure that varies the correlation between two structural error terms and measures how a predictor built under…	Curated	Evaluation Methods	`AIMech:BivariateCounterfactualFairnessSensitivity`	1 claim 1 source
Black box variational inference aka BBVI A variational-inference procedure that estimates evidence-lower-bound gradients from samples of a tractable variational distribution using i…	Curated	Algorithms	`AIMech:BlackBoxVariationalInference`	1 claim 2 sources
Blahut-Arimoto Rate-Distortion Algorithm aka Blahut Rate-Distortion Algorithm An alternating channel-and-marginal minimization algorithm for a fixed-source rate-distortion problem at a specified nonnegative distortion…	Curated	Algorithms	`AIMech:BlahutArimotoRateDistortionAlgorithm`	4 claims 2 sources
Block-matching and 3D filtering aka BM3D A grayscale image-denoising algorithm that stacks similar square patches into three-dimensional groups, jointly shrinks their transform coef…	Curated	Algorithms	`AIMech:BlockMatching3DFiltering`	6 claims 1 source
BOHB aka Bayesian Optimization and Hyperband A hyperparameter optimization algorithm combining Hyperband resource brackets with model-guided configuration proposals from performance-spl…	Curated	Algorithms	`AIMech:BOHB`	2 claims 4 sources
Boltzmann chain A family of tied-weight undirected Boltzmann sequence models with hidden temporal variables, observed variables and chain-derived connectivi…	Curated	Model Families	`AIMech:BoltzmannChain`	2 claims 2 sources
Boltzmann Machine Network aka BM, Sherrington–Kirkpatrick model with external field… A symmetrically connected network that is a type of stochastic recurrent neural network and Markov random field.	AIO	Network	`AIO:BoltzmannMachineNetwork`	Imported
Boosting Ensemble learning that sequentially adds learners to improve an existing predictor.	Curated	Learning Paradigms	`AIMech:Boosting`	1 claim 1 source
Bootstrap classifier-instability novelty detection aka Outlier detection using classifier instability, Bootstrap output-variance novelty detection A novelty-detection procedure that trains classifiers on bootstrap resamples of reference data, estimates the variance of their outputs at a…	Curated	Algorithms	`AIMech:BootstrapClassifierInstabilityNoveltyDetection`	4 claims 1 source
Bootstrap Your Own Latent aka BYOL A self-supervised image representation-learning procedure that trains an online predictor to match a stopped-gradient target projection from…	Curated	Algorithms	`AIMech:BootstrapYourOwnLatent`	1 claim 2 sources
Bottleneck Attention Module aka BAM (bottleneck attention) A convolutional feature refinement component that combines parallel channel and spatial attention branches and adds the resulting gated feat…	Curated	Layers & Modules	`AIMech:BottleneckAttentionModule`	2 claims 2 sources
Bounded adaptive reward for sequence scoring A beam-dependent sequence rescoring rule that adds per-step rewards derived from the beam’s mean negative log token probability, accumulatin…	Curated	Mathematical Methods	`AIMech:BoundedAdaptiveReward`	1 claim 1 source
Bounded length reward for sequence scoring aka Bounded word reward A sequence scoring rule that adds a fixed nonnegative reward per generated position up to a finite length cap, giving score S(y)+r·min(l,\|y\|…	Curated	Mathematical Methods	`AIMech:BoundedLengthReward`	2 claims 2 sources
Bounded word reward with predicted length A sequence rescoring method that adds a fixed word reward only up to an input-specific length predicted from encoder states, replacing a cor…	Curated	Mathematical Methods	`AIMech:PredictedLengthBoundedReward`	1 claim 1 source
Brandes betweenness centrality computation aka Brandes algorithm An exact graph algorithm for computing shortest-path vertex betweenness that combines single-source shortest-path counting with reverse-dist…	Curated	Algorithms	`AIMech:BrandesBetweennessCentrality`	7 claims 1 source
Brandes–Fleischer current-flow betweenness computation aka Brandes-Fleischer exact current-flow betweenness An exact network-analysis algorithm that computes current-flow betweenness by forming grounded-Laplacian current-response rows, sorting each…	Curated	Algorithms	`AIMech:BrandesFleischerCurrentFlowBetweenness`	6 claims 1 source
Brandes–Fleischer grounded current-flow closeness computation aka Brandes-Fleischer grounded resistance-sum closeness algorithm An exact network-analysis algorithm that accumulates effective-resistance sums from successive columns of an embedded grounded-Laplacian inv…	Curated	Algorithms	`AIMech:BrandesFleischerGroundedCurrentFlowCloseness`	6 claims 1 source
Brandes–Fleischer sampled-pair current-flow betweenness aka Brandes-Fleischer current-flow betweenness approximation A randomized network-analysis algorithm that estimates normalized, endpoint-excluded current-flow betweenness by independently sampling unif…	Curated	Algorithms	`AIMech:BrandesFleischerSampledCurrentFlowBetweenness`	6 claims 1 source
Brandes–Pich pivot-based centrality estimation aka Brandes-Pich centrality estimation A network-analysis procedure that estimates shortest-path closeness and betweenness from single-source computations at a selected subset of…	Curated	Algorithms	`AIMech:BrandesPichPivotCentralityEstimation`	7 claims 1 source
Breadth-first beam search aka Beam search A heuristic search procedure that advances by depth layers, retaining at most a chosen beam width of the best-ranked candidate nodes for eac…	Curated	Algorithms	`AIMech:BeamSearch`	2 claims 2 sources
Breadth-first branch-and-bound search aka BFBnB A heuristic graph-search procedure that expands states in breadth-first layers and prunes candidate paths whose accumulated cost plus an adm…	Curated	Algorithms	`AIMech:BreadthFirstBranchAndBound`	2 claims 2 sources
Breadth-first iterative-deepening A-star aka BFIDA, Breadth-first iterative-deepening A An iterative-deepening heuristic graph-search algorithm that repeatedly runs breadth-first branch-and-bound within increasing hypothetical f…	Curated	Algorithms	`AIMech:BreadthFirstIDAStar`	2 claims 2 sources
Breadth-first search aka BFS, Breadth first traversal A graph or state-space traversal that expands vertices in nondecreasing shortest-path distance from a start vertex, where distance counts ed…	Curated	Algorithms	`AIMech:BreadthFirstSearch`	2 claims 2 sources
Breakout method aka Breakout A finite constraint-satisfaction search method that takes strictly improving local assignment changes under a weighted nogood cost and incre…	Curated	Algorithms	`AIMech:BreakoutMethod`	1 claim 1 source
Brevity-penalty normalization for sequence scoring aka BP-Norm A sequence rescoring rule that adds a predicted-length brevity penalty in log space to average token log probability: S(x,y)/\|y\| + min(1−Lpr…	Curated	Mathematical Methods	`AIMech:BrevityPenaltyNormalization`	2 claims 2 sources
C4.5 Decision-tree induction extending ID3 with tests on continuous-valued features.	Curated	Algorithms	`AIMech:C45`	1 claim 1 source
CART aka Classification and Regression Trees Decision-tree induction using binary recursive partitioning for classification or regression.	Curated	Algorithms	`AIMech:CART`	1 claim 1 source
Categorical Features Preprocessing Layer A layer that performs categorical data preprocessing operations.	AIO	Layer	`AIO:CategoricalFeaturesPreprocessingLayer`	Imported
CategoryEncoding Layer A categorical features preprocessing layer that encodes integer features providing options for condensing data into a categorical encoding.	AIO	Layer	`AIO:CategoryEncodingLayer`	Imported
Causal Graphical Model aka Casaul Bayesian Network, Casaul Graph… A probabilistic graphical model used to encode assumptions about the data-generating process.	AIO	MachineLearningTask	`AIO:CausalGraphicalModel`	Imported
Causal LLM aka Causal Large Language Model, autoregressive… A large language model that only attends to previous tokens in the sequence when generating text modeling the probability distribution autor…	AIO	Model	`AIO:CausalLLM`	Imported
CD-PercLoss A conditional RBM training algorithm that contrasts the observed output free energy with that of a prediction selected by input-initialized…	Curated	Algorithms	`AIMech:CDPercLoss`	1 claim 1 source
CenterCrop Layer An image preprocessing layer that crops the central portion of images to a target size.	AIO	Layer	`AIO:CenterCropLayer`	Imported
Chakrabarti classifier-guided focused crawling aka Chakrabarti focused crawler, Taxonomy-guided focused crawling A focused web-acquisition procedure that uses a trained classifier over a supplied topic taxonomy to decide or prioritize hyperlink expansio…	Curated	Algorithms	`AIMech:ChakrabartiFocusedCrawler`	6 claims 1 source
CHAMELEON clustering aka CHAMELEON hierarchical clustering A graph-clustering procedure that first partitions a sparse neighbor graph into small subclusters and then agglomerates them using interconn…	Curated	Algorithms	`AIMech:CHAMELEONClustering`	1 claim 1 source
Circular weight-shift sampler A finite-state Markov transition construction that partitions a circle into intervals with target-weight lengths and derives each transition…	Curated	Algorithms	`AIMech:CircularWeightShiftSampler`	6 claims 4 sources
CLARANS clustering aka CLARANS, Clustering Large Applications based on RANdomized Search A randomized medoid-clustering algorithm that searches fixed-size sets of representative observations by accepting improving single swaps an…	Curated	Algorithms	`AIMech:CLARANSClustering`	2 claims 1 source
Classification A supervised learning focused on methods that distinguish and distribute kinds of "things" into different groups.	AIO	MachineLearningTask	`AIO:Classification`	Imported
Classification Annealing Expectation Maximization aka Classification Annealing EM, CAEM A stochastic hard-clustering algorithm that samples component assignments from current mixture posterior probabilities raised to an inverse…	Curated	Algorithms	`AIMech:ClassificationAnnealingExpectationMaximization`	3 claims 1 source
Classification Expectation Maximization aka Classification EM, CEM (classification expectation maximization) A model-based hard-clustering algorithm that computes mixture responsibilities, assigns every observation to a highest-responsibility compon…	Curated	Algorithms	`AIMech:ClassificationExpectationMaximization`	4 claims 1 source
Clauset–Newman–Moore community detection aka CNM, CNM community detection… A greedy community-detection algorithm that agglomerates graph vertices using modularity changes, with sparse change tables and heap-based m…	Curated	Algorithms	`AIMech:CNMCommunityDetection`	7 claims 2 sources
Cleaning aka Data Cleansing, Standardization… A data preparation that removes noise inconsistencies and irrelevant information from data to enhance its quality and prepare it for analysi…	AIO	Preprocessing	`AIO:Cleaning`	Imported
Clique extracted ontology aka CliXO An overlapping hierarchical clustering heuristic that constructs a directed acyclic hierarchy from pairwise dissimilarities by selecting inf…	Curated	Algorithms	`AIMech:CliXO`	7 claims 1 source
Clockwork recurrent neural network aka CW-RNN, Clockwork RNN A recurrent architecture partitioning hidden units into modules with prescribed update periods, copying inactive module states and restricti…	Curated	Architectures	`AIMech:ClockworkRecurrentNeuralNetwork`	6 claims 1 source
Clustering aka Cluster analysis A machine learning task focused on methods that group a set of objects such that objects in the same group are more similar to each other th…	AIO	MachineLearningTask	`AIO:Clustering`	Imported
Clustering Data by Melting aka Melting Algorithm for Clustering A scale-dependent clustering procedure that heats Gaussian-weighted center iterations to build a merging membership tree, then selects clust…	Curated	Algorithms	`AIMech:ClusteringDataByMelting`	4 claims 1 source
CMA rank-mu covariance update A covariance-valued update component introduced in the 2003 CMA-ES construction that forms an equal-weight second moment of selected mutatio…	Curated	Mathematical Methods	`AIMech:CMARankMuCovarianceUpdate`	6 claims 1 source
Cognitive Bias An individual bias characterized by deviations from rational judgment and decision-making including adaptive mental shortcuts known as heuri…	AIO	Bias	`AIO:CognitiveBias`	Imported
Communication Neural Network aka CommNet, Communication Neural Net… A neural architecture for cooperative multi-agent tasks that alternates shared per-agent hidden-state updates with continuous communication…	Curated	Architectures	`AIMech:CommunicationNeuralNetwork`	6 claims 1 source
Competitive learning An unsupervised learning paradigm in which units or modules compete to represent presented input patterns and adapt their representations ac…	Curated	Learning Paradigms	`AIMech:CompetitiveLearning`	5 claims 2 sources
Complete balanced largest differencing aka Complete BLDM A complete anytime two-way number-partitioning search that carries signed effective cardinalities through difference and sum branches, uses…	Curated	Algorithms	`AIMech:CompleteBalancedLargestDifferencing`	6 claims 1 source
Complete greedy number partitioning aka CGA, Complete greedy algorithm for number partitioning A complete anytime number-partitioning search that assigns weights in decreasing order to a fixed number of bins, explores the currently lig…	Curated	Algorithms	`AIMech:CompleteGreedyNumberPartitioning`	6 claims 1 source
Complete Karmarkar–Karp aka CKK A complete anytime algorithm for two-way number partitioning that first follows Karmarkar–Karp differencing, then explores complementary sum…	Curated	Algorithms	`AIMech:CompleteKarmarkarKarp`	6 claims 1 source
Complete layer-wise adaptive rate scaling aka CLARS A layer-wise gradient optimization method whose published rate formula divides the current parameter-block L2 norm by the average L2 norm of…	Curated	Algorithms	`AIMech:CompleteLayerWiseAdaptiveRateScaling`	7 claims 3 sources
Complete multiway Karmarkar–Karp aka Multiway CKK A complete anytime multiway number-partitioning search that combines partial bin assignments in alternative relative permutations, explores…	Curated	Algorithms	`AIMech:CompleteMultiwayKarmarkarKarp`	6 claims 1 source
Composite HMM-topic model A generative sequence model combining an HMM class sequence with a document topic mixture, where one designated class emits words through la…	Curated	Model Families	`AIMech:CompositeHMMTopicModel`	2 claims 1 source
Compositional Generalization LLM aka Compositional Generalization Large Language Model, out-of-distribution generalization… A large language model that is trained to understand and recombine the underlying compositional structures in language enabling better gener…	AIO	Model	`AIO:CompositionalGeneralizationLLM`	Imported
Compositional spatial transformer A learnable image-alignment module that retains an original source image and accumulated warp state, samples that source under the current w…	Curated	Layers & Modules	`AIMech:CompositionalSpatialTransformer`	5 claims 1 source
Computational Bias aka Statistical Bias A bias caused by differences between results and facts in the process of data analysis (including the source of data the estimator chose) an…	AIO	Bias	`AIO:ComputationalBias`	Imported
Concatenate Layer A merging layer that concatenates a list of inputs taking as input a list of tensors all of the same shape except for the concatenation axis…	AIO	Layer	`AIO:ConcatenateLayer`	Imported
Concept Drift Bias aka Concept Drift A use and interpretation bias due to the use of a system outside its planned domain of application causing performance gaps between laborato…	AIO	Bias	`AIO:ConceptDriftBias`	Imported
Condensed nearest-neighbor data domain description aka CNNDD, Condensed NNDD rule A greedy reference-selection algorithm for the NNDD distance-norm decision rule that uses two passes over the original observations followed…	Curated	Algorithms	`AIMech:CondensedNearestNeighborDataDomainDescription`	5 claims 1 source
Condensed prototype-based domain description aka CPDD, Greedy prototype domain condensation A greedy prototype-selection procedure that constructs kth-neighbor radius offsets from the full reference dataset and repeatedly chooses th…	Curated	Algorithms	`AIMech:CondensedPrototypeBasedDomainDescription`	4 claims 1 source
Conditional Distribution Prediction for IDA* aka Conditional Distribution Prediction A search-effort estimation procedure that predicts the number of expanded nodes in a complete IDA* threshold iteration by recursively propag…	Curated	Algorithms	`AIMech:ConditionalDistributionPredictionIDAStar`	5 claims 1 source
Conditional restricted Boltzmann machine aka CRBM, Conditional RBM A conditional neural probability model that represents an output vector with an RBM whose biases or interactions are determined by a supplie…	Curated	Architectures	`AIMech:ConditionalRestrictedBoltzmannMachine`	1 claim 1 source
Confirmation Bias An individual bias characterized by the tendency to prefer information that confirms existing beliefs influencing the search for interpretat…	AIO	Bias	`AIO:ConfirmationBias`	Imported
Conjugate-gradient Monte Carlo aka CGMC A population Markov sampler that obtains a local-optimization anchor from one population member and updates another member along the anchor…	Curated	Algorithms	`AIMech:ConjugateGradientMonteCarlo`	1 claim 1 source
Consistency model aka Consistency models, CM (consistency model) A generative model family that learns a noise- or time-conditioned function mapping points on a probability-flow ODE trajectory to its commo…	Curated	Model Families	`AIMech:ConsistencyModel`	2 claims 2 sources
Consumer Bias An individual bias arising when an algorithm or platform provides users a venue to express their biases occurring from either side in a digi…	AIO	Bias	`AIO:ConsumerBias`	Imported
Content Production Bias A use and interpretation bias arising from structural lexical semantic and syntactic differences in user-generated content.	AIO	Bias	`AIO:ContentProductionBias`	Imported
Context-sensitive emission hidden Markov model A hidden-state sequence-model family with a first-order Markov prior whose observation distributions depend jointly on hidden states at mult…	Curated	Model Families	`AIMech:ContextSensitiveEmissionHiddenMarkovModel`	1 claim 1 source
Continual Learning aka Incremental Learning, Life-Long Learning A deep neural network that learns sequential tasks without forgetting knowledge from preceding tasks and without access to old task data dur…	AIO	Network	`AIO:ContinualLearning`	Imported
Continual Learning LLM aka CL-Large Language Model, Continual Learning Large Language Model… A large language model that continually acquires new knowledge and skills over time without forgetting previously learned information allowi…	AIO	Model	`AIO:ContinualLearningLLM`	Imported
Continuous-time Bayesian network A finite-state continuous-time model family combining a separate initial Bayesian-network distribution with a directed, possibly cyclic grap…	Curated	Model Families	`AIMech:ContinuousTimeBayesianNetwork`	6 claims 1 source
Contrastive divergence aka CD, CD-k A parameter-learning algorithm for energy-based or product-of-experts models that replaces the equilibrium negative-phase expectation by con…	Curated	Algorithms	`AIMech:ContrastiveDivergence`	2 claims 3 sources
Contrastive Learning A deep neural network self-supervised learning approach that learns to distinguish between similar and dissimilar data samples.	AIO	Network	`AIO:ContrastiveLearning`	Imported
Contrastive Learning LLM aka Representation learning A large language model that is trained to pull semantically similar samples closer together and push dissimilar samples apart in the represe…	AIO	Model	`AIO:ContrastiveLearningLLM`	Imported
Contrastive predictive coding aka CPC A representation-learning procedure that encodes observations, summarizes preceding representations as context, and jointly trains these com…	Curated	Algorithms	`AIMech:ContrastivePredictiveCoding`	1 claim 2 sources
Controllable LLM aka Controllable Large Language Model, conditional generation… A large language model that allows for explicit control over certain attributes of the generated text such as style tone topic or other desi…	AIO	Model	`AIO:ControllableLLM`	Imported
ConvLSTM1D Layer A convolutional layer that implements a 1D Convolutional LSTM similar to an LSTM but with convolutional input and recurrent transformations.	AIO	Layer	`AIO:ConvLSTM1DLayer`	Imported
ConvLSTM2D Layer A convolutional layer that implements a 2D Convolutional LSTM similar to an LSTM but with convolutional input and recurrent transformations.	AIO	Layer	`AIO:ConvLSTM2DLayer`	Imported
ConvLSTM3D Layer A convolutional layer that implements a 3D Convolutional LSTM similar to an LSTM but with convolutional input and recurrent transformations.	AIO	Layer	`AIO:ConvLSTM3DLayer`	Imported
Convolution1D Layer aka Conv1D, Conv1D Layer… A convolutional layer that implements 1D convolution (e.g. temporal convolution).	AIO	Layer	`AIO:Convolution1DLayer`	Imported
Convolution1DTranspose Layer aka Conv1DTranspose Layer, ConvTranspose1D… A convolutional layer that implements transposed 1D convolution sometimes called deconvolution.	AIO	Layer	`AIO:Convolution1DTransposeLayer`	Imported
Convolution2D Layer aka Conv2D, Conv2D Layer… A convolutional layer that implements 2D convolution (e.g. spatial convolution over images).	AIO	Layer	`AIO:Convolution2DLayer`	Imported
Convolution2DTranspose Layer aka Conv2DTranspose Layer, ConvTranspose2D… A convolutional layer that implements transposed 2D convolution	AIO	Layer	`AIO:Convolution2DTransposeLayer`	Imported
Convolution3D Layer aka Conv3D, Conv3D Layer… A convolutional layer that implements 3D convolution (e.g. spatial convolution over volumes).	AIO	Layer	`AIO:Convolution3DLayer`	Imported
Convolution3DTranspose Layer aka Conv3DTranspose Layer, ConvTranspose3D… A convolutional layer that implements transposed 3D convolution	AIO	Layer	`AIO:Convolution3DTransposeLayer`	Imported
Convolutional Block Attention Module aka CBAM A convolutional feature refinement component that sequentially applies learned channel attention and then spatial attention to an intermedia…	Curated	Layers & Modules	`AIMech:ConvolutionalBlockAttentionModule`	2 claims 2 sources
Convolutional Layer A layer that contains a set of filters (or kernels) parameters of which are to be learned throughout the training.	AIO	Layer	`AIO:ConvolutionalLayer`	Imported
Core vector machine aka CVM An approximate kernel training algorithm that reformulates supported constant-diagonal simplex quadratic programs as minimum enclosing balls…	Curated	Algorithms	`AIMech:CoreVectorMachine`	8 claims 4 sources
Core vector regression aka CVR A support-vector regression training algorithm that approximates a penalized-bias, paired squared-slack formulation with a learned unconstra…	Curated	Algorithms	`AIMech:CoreVectorRegression`	6 claims 2 sources
Core-set support vector data description aka CSVDD An approximate one-class training algorithm that grows a core subset using the nearest expanded-sphere violator, refits support vector data…	Curated	Algorithms	`AIMech:CoreSetSupportVectorDataDescription`	7 claims 1 source
Correlated topic model aka CTM A mixed-membership topic model that draws each document's topic proportions from a logistic-normal distribution and generates its words thro…	Curated	Model Families	`AIMech:CorrelatedTopicModel`	2 claims 3 sources
Correlation-based Hammerstein identification A two-stage identification algorithm for a real-valued single-input single-output polynomial Hammerstein cascade that estimates a scaled lin…	Curated	Algorithms	`AIMech:CorrelationBasedHammersteinIdentification`	4 claims 2 sources
Correlation-based Wiener identification A two-stage identification algorithm for a real-valued single-input single-output polynomial Wiener cascade that estimates a scaled linear r…	Curated	Algorithms	`AIMech:CorrelationBasedWienerIdentification`	4 claims 2 sources
Counterfactual fairness aka CF (counterfactual fairness) A fairness criterion in a specified causal model requiring a predictor's conditional output distribution, given an individual's observed att…	Curated	Evaluation Criteria	`AIMech:CounterfactualFairness`	3 claims 3 sources
Covariance Matrix Adaptation Evolution Strategy aka CMA-ES An evolution strategy for continuous optimization that samples a multivariate normal search distribution and adapts its mean, covariance and…	Curated	Algorithms	`AIMech:CovarianceMatrixAdaptationEvolutionStrategy`	1 claim 1 source
Crank–Nicolson Langevin sampling aka CNL A Metropolis-corrected Gaussian-reference sampler that combines a Crank–Nicolson treatment of the reference precision with an explicit gradi…	Curated	Algorithms	`AIMech:CrankNicolsonLangevin`	1 claim 1 source
Crank–Nicolson Metropolis sampling aka CN sampler A Metropolis sampler for a Gaussian-reference target using a Crank–Nicolson discretization of the unpreconditioned reference Ornstein–Uhlenb…	Curated	Algorithms	`AIMech:CrankNicolsonMetropolis`	1 claim 1 source
Cropping1D Layer A reshaping layer that crops along the time dimension (axis 1) for 1D input.	AIO	Layer	`AIO:Cropping1DLayer`	Imported
Cropping2D Layer A layer that crops along spatial dimensions (i.e. height and width) for 2D input.	AIO	Layer	`AIO:Cropping2DLayer`	Imported
Cropping3D Layer A layer that crops along spatial dimensions (depth, height and width) for 3D input.	AIO	Layer	`AIO:Cropping3DLayer`	Imported
Cross-Domain LLM aka Domain-General LLM, cross-domain transfer… A large language model that performs well across a wide range of domains without significant loss in performance, facilitated by advanced do…	AIO	Model	`AIO:CrossDomainLLM`	Imported
Cross-entropy optimization aka Cross-entropy method for optimization A stochastic optimization method that iteratively samples a parameterized search distribution, selects high-performing samples using an adap…	Curated	Algorithms	`AIMech:CrossEntropyOptimization`	1 claim 1 source
Cross-entropy rare-event importance sampling A rare-event probability estimation algorithm that fits a parametric importance-sampling proposal by cross-entropy minimization toward the n…	Curated	Algorithms	`AIMech:CrossEntropyImportanceSampling`	6 claims 1 source
Cross-validated prior-likelihood conflict diagnostic A Bayesian hierarchical-model diagnostic that leaves an assessed unit out of population-parameter fitting, generates predictive-prior and re…	Curated	Algorithms	`AIMech:CrossValidatedPriorLikelihoodConflictDiagnostic`	7 claims 3 sources
CTAugment An online augmentation-policy adaptation procedure that samples image operations and adjusts their parameter-selection weights using classif…	Curated	Algorithms	`AIMech:CTAugment`	2 claims 6 sources
CURE clustering aka CURE, Clustering Using REpresentatives An agglomerative clustering procedure that represents each cluster by several scattered points shrunk toward its mean and merges the pair wi…	Curated	Algorithms	`AIMech:CUREClustering`	1 claim 1 source
Curriculum Dropout A neural-network training procedure that starts without unit suppression and gradually increases Bernoulli dropout by decreasing the probabi…	Curated	Algorithms	`AIMech:CurriculumDropout`	5 claims 2 sources
Curriculum Learning aka Sequential Learning, Structured Learning… A training strategy in machine learning where models are trained on data in a meaningful order starting with simpler examples and gradually…	AIO	TrainingStrategy	`AIO:CurriculumLearning`	Imported
Curriculum Learning LLM aka Learning progression A large language model that is trained by presenting learning examples in a meaningful order from simple to complex mimicking the learning t…	AIO	Model	`AIO:CurriculumLearningLLM`	Imported
CutMix A training augmentation procedure that replaces a rectangular region of one image with the corresponding region of another and mixes their c…	Curated	Algorithms	`AIMech:CutMix`	2 claims 2 sources
Cutout A training-image augmentation method that removes information from a randomly located square region by replacing that region with zeros in t…	Curated	Preprocessing Methods	`AIMech:Cutout`	1 claim 1 source
Cutting Plane Multiclass Maximum Margin Clustering aka CPM3C A fixed-kernel multiclass clustering procedure that fits latent winning-class margins by adding violated aggregate constraints and repeatedl…	Curated	Algorithms	`AIMech:CuttingPlaneMulticlassMaximumMarginClustering`	4 claims 1 source
Data Augmentation aka Data Enrichment, Data Expansion… A data enhancement used to increase the diversity and quantity of training data by applying various transformations such as rotation scaling…	AIO	Preprocessing	`AIO:DataAugmentation`	Imported
Data Dredging Bias aka Data Dredging A use and interpretation bias where testing many hypotheses in a dataset may yield apparent statistical significance even when results are n…	AIO	Bias	`AIO:DataDredgingBias`	Imported
Data Generation Bias A selection and sampling bias arising from adding synthetic or redundant data samples to a dataset.	AIO	Bias	`AIO:DataGenerationBias`	Imported
Data Imputation A machine learning task focused on methods that replace missing data with substituted values.	AIO	MachineLearningTask	`AIO:DataImputation`	Imported
Data Preparation aka Data Assembly, Data Curation… A preprocessing that cleans, transforms and organizes raw data into a suitable format for analysis and modeling, ensuring the quality and re…	AIO	Preprocessing	`AIO:DataPreparation`	Imported
Data-to-Text LLM aka Meaning representation A large language model that generates natural language descriptions from structured data sources like tables, graphs, and knowledge bases, r…	AIO	Model	`AIO:DatatoTextLLM`	Imported
DataEnhancement A preprocessing used to improve the quality diversity and volume of data available for training machine learning models, such as data augmen…	AIO	Preprocessing	`AIO:DataEnhancement`	Imported
DBSCAN aka Density-Based Spatial Clustering of Applications with Noise Density-based clustering that connects dense neighborhoods and identifies unsupported observations as noise.	Curated	Algorithms	`AIMech:DBSCAN`	1 claim 1 source
Decision Tree A classification that uses a tree-like model of decisions and their possible consequences including chance event outcomes resource costs and…	AIO	MachineLearningTask	`AIO:DecisionTree`	Imported
Decoder LLM A large language model that uses a decoder-only architecture consisting of only a decoder trained to predict the next token in a sequence gi…	AIO	Model	`AIO:DecoderLLM`	Imported
Deconvolutional Network aka DN A deep neural network that uses deconvolution for unsupervised construction of hierarchical image representations.	AIO	Network	`AIO:DeconvolutionalNetwork`	Imported
Deep Active Learning aka DeepAL A deep neural network that combines deep learning and active learning to maximize model performance while annotating the fewest samples poss…	AIO	Network	`AIO:DeepActiveLearning`	Imported
Deep autoregressive network aka DARN A generative neural architecture that combines directed stochastic hidden layers with autoregressive within-layer conditional dependencies a…	Curated	Architectures	`AIMech:DeepAutoregressiveNetwork`	1 claim 1 source
Deep Belief Network aka DBN An unsupervised pretrained network composed of multiple layers of latent variables that learns to probabilistically reconstruct inputs and p…	AIO	Network	`AIO:DeepBeliefNetwork`	Imported
Deep continuous clustering A clustering algorithm that jointly learns a nonlinear autoencoder and one latent representative per observation by combining reconstruction…	Curated	Algorithms	`AIMech:DeepContinuousClustering`	7 claims 7 sources
Deep Convolutional Inverse Graphics Network aka DCIGN An autoencoder network that learns interpretable disentangled image representations through convolution and de-convolution layers trained wi…	AIO	Network	`AIO:DeepConvolutionalInverseGraphicsNetwork`	Imported
Deep Convolutional Network aka CNN, ConvNet… A deep neural network specialized for analyzing visual imagery using shared-weight architecture and translation-equivariant feature maps.	AIO	Network	`AIO:DeepConvolutionalNetwork`	Imported
Deep deterministic policy gradient aka DDPG An off-policy actor–critic method for continuous control using neural function approximators and deterministic policy gradients.	Curated	Algorithms	`AIMech:DeepDeterministicPolicyGradient`	1 claim 1 source
Deep embedded clustering aka DEC, Unsupervised deep embedding for clustering analysis A neural clustering procedure that jointly refines an embedding and cluster centers by fitting Student-t soft assignments to periodically re…	Curated	Algorithms	`AIMech:DeepEmbeddedClustering`	1 claim 2 sources
Deep Feed-Forward Network aka DFF, MLP… A deep neural network that processes information in one direction—from input nodes through hidden nodes to output nodes—without cycles or lo…	AIO	Network	`AIO:DeepFeedForwardNetwork`	Imported
Deep InfoMax aka DIM A representation-learning procedure that jointly trains an encoder and a dependence critic on matched versus mismatched global or local-to-g…	Curated	Algorithms	`AIMech:DeepInfoMax`	1 claim 5 sources
Deep Neural Network aka DNN An artificial neural network characterized by multiple hidden layers between the input and output layers.	AIO	Network	`AIO:DeepNeuralNetwork`	Imported
Deep Output Recurrent Neural Network aka DO-RNN A recurrent neural architecture whose hidden-to-output function uses a multilayer perceptron with intermediate nonlinear feedforward layers…	Curated	Architectures	`AIMech:DeepOutputRecurrentNeuralNetwork`	4 claims 1 source
Deep Output-Transition Recurrent Neural Network aka DOT-RNN, Deep output, deep transition RNN A recurrent neural architecture that uses intermediate nonlinear feedforward layers in both the hidden-state transition from the previous st…	Curated	Architectures	`AIMech:DeepOutputTransitionRecurrentNeuralNetwork`	6 claims 1 source
Deep Q-network learning aka DQN, Deep Q-network A deep Q-learning method that trains a neural action-value function using replayed transitions and a separate target network.	Curated	Algorithms	`AIMech:DeepQNetwork`	1 claim 1 source
Deep Sets A neural architecture family for unordered collections that combines shared element transformations with symmetric aggregation for invariant…	Curated	Architectures	`AIMech:DeepSets`	1 claim 1 source
Deep Sets++ aka DS++ A Deep Sets architecture revision whose encoder combines identity residual paths with set normalization while retaining the original aggrega…	Curated	Architectures	`AIMech:DeepSetsPlusPlus`	1 claim 1 source
Deep SHAP A compositional approximation of neural-network Shapley attributions using component-level SHAP values and backward multipliers.	Curated	Algorithms	`AIMech:DeepSHAP`	1 claim 1 source
Deep Transfer Learning A deep neural network that relaxes the hypothesis that training data must be independent and identically distributed with test data to addre…	AIO	Network	`AIO:DeepTransferLearning`	Imported
Deep Transition Recurrent Neural Network aka DT-RNN A recurrent neural architecture whose state-transition function uses a multilayer perceptron with intermediate nonlinear feedforward layers…	Curated	Architectures	`AIMech:DeepTransitionRecurrentNeuralNetwork`	4 claims 1 source
DeepCluster aka Deep clustering for unsupervised learning of visual features A visual representation-learning procedure that alternates clustering current neural features into pseudo-labels and training the feature ex…	Curated	Algorithms	`AIMech:DeepCluster`	1 claim 4 sources
DeepLIFT aka Deep Learning Important FeaTures A neural-network attribution method that distributes an output's difference from a reference activation to input differences using backward…	Curated	Algorithms	`AIMech:DeepLIFT`	1 claim 1 source
Definition-filtered Girvan–Newman community detection aka self-contained Girvan–Newman algorithm, strong/weak community validation for Girvan–Newman A Girvan–Newman variant that retains a branching event in the reported hierarchy only when at least two resulting groups satisfy a selected…	Curated	Algorithms	`AIMech:DefinitionFilteredGirvanNewman`	6 claims 1 source
DEHB aka Evolutionary Hyperband A hyperparameter optimization algorithm that combines Hyperband resource schedules with differential-evolution populations at different reso…	Curated	Algorithms	`AIMech:DEHB`	1 claim 2 sources
Delayed-rejection adaptive Metropolis aka DRAM An adaptive Metropolis procedure combining history-based Gaussian proposal covariance updates between transitions with corrected delayed-rej…	Curated	Algorithms	`AIMech:DelayedRejectionAdaptiveMetropolis`	1 claim 2 sources
Delayed-rejection Metropolis aka Delayed rejection Metropolis-Hastings A Metropolis-Hastings sampling procedure that can propose another candidate after rejection within the same transition, correcting acceptanc…	Curated	Algorithms	`AIMech:DelayedRejectionMetropolis`	1 claim 1 source
Demographic parity aka Statistical parity A group-level prediction criterion requiring the distribution of a decision or prediction to be independent of a specified protected attribu…	Curated	Evaluation Criteria	`AIMech:DemographicParity`	3 claims 3 sources
Denoising Auto Encoder aka DAE, Denoising Autoencoder An autoencoder network trained to reconstruct the original undistorted input from a partially corrupted input.	AIO	Network	`AIO:DenoisingAutoEncoder`	Imported
Dense Layer A layer that is a regular densely-connected neural network layer.	AIO	Layer	`AIO:DenseLayer`	Imported
DenseFeatures Layer A layer that produces a dense tensor based on given feature columns.	AIO	Layer	`AIO:DenseFeaturesLayer`	Imported
Deployment Bias A group bias arising when systems are used as decision aids for humans since the human intermediary may act on predictions in ways that are…	AIO	Bias	`AIO:DeploymentBias`	Imported
Depth-first iterative deepening aka DFID, Iterative deepening depth-first search… A search algorithm that repeatedly performs depth-first searches from the start with successively larger depth limits, redoing shallower wor…	Curated	Algorithms	`AIMech:DepthFirstIterativeDeepening`	2 claims 2 sources
Depth-first search aka DFS, Depth first traversal A graph or state-space traversal that follows a newly chosen successor down the current search branch and backtracks when that branch has no…	Curated	Algorithms	`AIMech:DepthFirstSearch`	2 claims 2 sources
Depth-Gated LSTM aka DGLSTM, Depth-gated long short-term memory A stacked LSTM architecture that adds a learned, elementwise gated contribution from the current lower-layer memory cell to the upper-layer…	Curated	Architectures	`AIMech:DepthGatedLSTM`	6 claims 1 source
DepthwiseConv1D Layer A convolutional layer that performs depthwise 1D convolution	AIO	Layer	`AIO:DepthwiseConv1DLayer`	Imported
DepthwiseConv2D Layer A convolutional layer that performs depthwise 2D convolution	AIO	Layer	`AIO:DepthwiseConv2DLayer`	Imported
Derivative-observation Gaussian process regression aka Gaussian process regression with derivative observations A Gaussian-process regression procedure that jointly conditions a sufficiently differentiable scalar-function prior on function values and p…	Curated	Algorithms	`AIMech:DerivativeObservationGaussianProcessRegression`	5 claims 1 source
Detection Bias A selection and sampling bias characterized by systematic differences between groups in how outcomes are determined potentially over- or und…	AIO	Bias	`AIO:DetectionBias`	Imported
Deterministic Annealing Expectation Maximization aka Deterministic Annealing EM, DAEM A latent-variable likelihood-fitting procedure that performs deterministic powered-posterior EM updates along a warm-started cooling schedul…	Curated	Algorithms	`AIMech:DeterministicAnnealingExpectationMaximization`	4 claims 1 source
Diaconis–Holmes–Neal fiber sampler A finite-state Metropolis sampler that uses partitions into ordered lines, retains a binary direction for each partition, and combines a nei…	Curated	Algorithms	`AIMech:DiaconisHolmesNealFiberSampler`	6 claims 1 source
Diagonal structured state space model aka S4D A diagonal state-space sequence-model family that computes its discretized convolution kernel by a Vandermonde product, with explicit choice…	Curated	Model Families	`AIMech:S4D`	1 claim 1 source
Dialogue LLM aka Dialogue Large Language Model, conversational AI… A large language model that is optimized for engaging in multi-turn conversations understanding context and generating relevant coherent res…	AIO	Model	`AIO:DialogueLLM`	Imported
Differentiable LLM aka Differentiable Large Language Model, end-to-end training… A large language model that has an architecture amenable to full end-to-end training via backpropagation without relying on teacher forcing…	AIO	Model	`AIO:DifferentiableLLM`	Imported
Differentiable scheduled sampling A scheduled-sampling training procedure that replaces discrete model-feedback embeddings with differentiable soft mixtures, allowing later s…	Curated	Algorithms	`AIMech:DifferentiableScheduledSampling`	6 claims 1 source
Differential Evolution aka DE A population-based continuous optimization method that generates trial vectors using scaled differences between population members, combines…	Curated	Algorithms	`AIMech:DifferentialEvolution`	1 claim 1 source
Diffusion Maps aka Diffusion Map A family of spectral embedding algorithms that normalizes a nonnegative symmetric affinity kernel into a reversible Markov operator and repr…	Curated	Algorithms	`AIMech:DiffusionMaps`	1 claim 1 source
Dijkstra shortest-path algorithm aka Dijkstra's algorithm, Dijkstra shortest path A shortest-path algorithm for nonnegative edge weights that repeatedly settles the unsettled vertex with the smallest tentative distance fro…	Curated	Algorithms	`AIMech:DijkstraShortestPath`	2 claims 2 sources
Dimensionality Reduction aka Dimension Reduction An unsupervised learning focused on the process of transforming data from a high-dimensional space into a lower-dimensional space while reta…	AIO	MachineLearningTask	`AIO:DimensionalityReduction`	Imported
DINO self-distillation aka Self-distillation with no labels A self-supervised representation-learning procedure that matches cross-view student probabilities to centered and sharpened probabilities fr…	Curated	Algorithms	`AIMech:DINOSelfDistillation`	1 claim 2 sources
DIRECT global optimization A deterministic derivative-free global optimization algorithm that adaptively partitions a bounded real search box, samples rectangle center…	Curated	Algorithms	`AIMech:DIRECTGlobalOptimization`	6 claims 1 source
Direct preference optimization aka DPO Preference-based policy fitting using a classification objective on policy-to-reference probability ratios for preferred and dispreferred re…	Curated	Algorithms	`AIMech:DirectPreferenceOptimization`	1 claim 1 source
Dirichlet compound multinomial latent Dirichlet allocation aka DCM-LDA A topic-model family for grouped documents in which each group draws its own topic-word distributions from corpus-shared topic-specific Diri…	Curated	Model Families	`AIMech:DirichletCompoundMultinomialLDA`	3 claims 1 source
Discretization Layer A numerical features preprocessing layer which buckets continuous features by ranges.	AIO	Layer	`AIO:DiscretizationLayer`	Imported
Dispatch-dependent dual-queue planning A concurrent temporal-planning search procedure that alternates node expansion between a weighted goal-progress open list and a dispatch-con…	Curated	Algorithms	`AIMech:DispatchDependentDualQueuePlanning`	5 claims 1 source
Dispatch-dependent value functional A dispatch-prefix-conditioned mathematical rule that returns, as a function of a contemplated search start time t, the modeled probability o…	Curated	Mathematical Methods	`AIMech:DispatchDependentValueFunctional`	6 claims 1 source
Distillation aka Purification, Refining… A preprocessing that trains a smaller model to replicate the behavior of a larger model aiming to compress the knowledge into a more compact…	AIO	TrainingStrategy	`AIO:Distillation`	Imported
Diverse beam search aka DBS The inference procedure of Vijayakumar and colleagues that partitions a sequence beam budget into groups and updates each group using model…	Curated	Algorithms	`AIMech:DiverseBeamSearch`	3 claims 1 source
Divide-and-conquer beam search A memory-limited breadth-first heuristic search that discards least-promising open nodes when its chosen capacity is reached and recovers a…	Curated	Algorithms	`AIMech:DivideConquerBeamSearch`	3 claims 3 sources
Divide-and-conquer beam-stack search aka DCBSS A beam-stack search implementation that retains a small set of search layers and relay information, regenerates missing layers for backtrack…	Curated	Algorithms	`AIMech:DivideConquerBeamStackSearch`	2 claims 2 sources
Document NADE aka DocNADE A neural autoregressive document model that predicts successive words from shared additive embeddings of the preceding words, using normaliz…	Curated	Architectures	`AIMech:DocumentNADE`	1 claim 2 sources
Domain-Adapted LLM aka Domain-Adapted Large Language Model, domain robustness… A large language model which is pre-trained on a broad corpus and then fine-tuned on domain-specific data to specialize its capabilities for…	AIO	Model	`AIO:DomainAdaptedLLM`	Imported
Dot Layer A layer that computes a dot product between samples in two tensors.	AIO	Layer	`AIO:DotLayer`	Imported
Doubling slice sampling A univariate slice-sampling algorithm that expands a randomly placed initial interval by randomly directed doublings and uses shrinkage with…	Curated	Algorithms	`AIMech:DoublingSliceSampling`	1 claim 1 source
DropBlock A training-time feature-map transformation for convolutional networks that suppresses randomly placed contiguous spatial blocks of activatio…	Curated	Layers & Modules	`AIMech:DropBlock`	1 claim 2 sources
DropConnect A stochastic neural-network layer that masks individual weights and biases during training, so each example is processed through a randomly…	Curated	Layers & Modules	`AIMech:DropConnect`	1 claim 1 source
Dropout Boosting A dropout-mask training procedure proposed to optimize the likelihood of a normalized geometric ensemble, updating through a selected shared…	Curated	Algorithms	`AIMech:DropoutBoosting`	5 claims 1 source
Dropout Layer A regularization layer that applies Dropout to the input	AIO	Layer	`AIO:DropoutLayer`	Imported
DUAL* The source’s MAX-rooted application of the dual of SSS*, using LIVE/SOLVED node descriptors, maximum-based merit updates and dual MAX/MIN ex…	Curated	Algorithms	`AIMech:DUALStar`	6 claims 1 source
Dual-averaging step-size adaptation for Hamiltonian samplers A warmup procedure that tunes the logarithm of a Hamiltonian sampler’s integration step size using cumulative discrepancy from a target acce…	Curated	Algorithms	`AIMech:DualAveragingHamiltonianStepSize`	1 claim 1 source
Dunning-Kruger Effect Bias aka Dunning-Kruger Effect A cognitive bias in which people with low ability in an area overestimate that ability. Often measured by comparing self-assessment with obj…	AIO	Bias	`AIO:DunningKrugerEffectBias`	Imported
Dutch eligibility traces An eligibility-trace update that propagates prior feature credit and adds a current-feature contribution adjusted by the prior trace’s proje…	Curated	Mathematical Methods	`AIMech:DutchEligibilityTraces`	5 claims 3 sources
Dynamic Conditional Correlation aka DCC A model that allows for time-varying correlations between different time series, used in financial econometrics to model and forecast covari…	AIO	Model	`AIO:DynamicConditionalCorrelation`	Imported
Dynamic Convolutional Layer aka Dynamic Convolution Layer A neural layer that convolves feature maps with filters generated from the current input by a learned subnetwork, allowing the applied kerne…	Curated	Layers & Modules	`AIMech:DynamicConvolutionalLayer`	6 claims 1 source
Dynamic Memory Network aka DMN, Dynamic Memory Networks A recurrent neural architecture that encodes an input and a question, repeatedly forms question-conditioned episodes from input facts to upd…	Curated	Architectures	`AIMech:DynamicMemoryNetwork`	6 claims 1 source
Dynamic Memory Network Plus aka DMN+ A recurrent question-answering architecture that fuses text or image facts, aggregates them with question- and memory-conditioned attention…	Curated	Architectures	`AIMech:DynamicMemoryNetworkPlus`	6 claims 1 source
Dynamic topic model aka DTM A time-sliced topic-model family that links the softmax natural parameters of corresponding topic-word distributions across slices through G…	Curated	Model Families	`AIMech:DynamicTopicModel`	2 claims 1 source
Early Dropout A neural-network training procedure that applies dropout during an initial portion of optimization and disables it for the remaining trainin…	Curated	Algorithms	`AIMech:EarlyDropout`	5 claims 1 source
Echo State Network aka ESN A recurrent neural network with a recurrent hidden layer and sparsely connected hidden neurons that learns output weights to produce tempora…	AIO	Network	`AIO:EchoStateNetwork`	Imported
Eclat Frequent-itemset mining using depth-first enumeration and transaction-set intersections.	Curated	Algorithms	`AIMech:Eclat`	1 claim 1 source
Ecological Fallacy Bias aka Ecological Fallacy A selection and sampling bias occurring when an inference about an individual is made based on their group membership.	AIO	Bias	`AIO:EcologicalFallacyBias`	Imported
Efficient Global Optimization The original sequential optimization algorithm of Jones, Schonlau and Welch for expensive deterministic scalar functions on bounded continuo…	Curated	Algorithms	`AIMech:EfficientGlobalOptimization`	6 claims 1 source
Elastic net aka Elastic-net regression Linear regression regularized by a combination of L1 and L2 penalties.	Curated	Mathematical Methods	`AIMech:ElasticNet`	1 claim 1 source
Elitist Ant System aka ASelite An Ant System variant that retains the standard all-ant pheromone deposits and adds extra reinforcement to edges of the best-so-far tour aft…	Curated	Algorithms	`AIMech:ElitistAntSystem`	1 claim 2 sources
Elliptical slice sampling aka ESS A Markov-chain update for a target factored into a Gaussian prior and a likelihood, which performs an angular slice search along the ellipse…	Curated	Algorithms	`AIMech:EllipticalSliceSampling`	1 claim 1 source
ELU Function aka ELU, Exponential Linear Unit A mathematical function that is x if x > 0 and alpha * (exp(x) - 1) if x < 0 where alpha controls the value to which an ELU saturates for ne…	AIO	MathematicalFunction	`AIO:ELUFunction`	Imported
ELU Layer An activation layer that applies the Exponential Linear Unit (ELU) function element-wise.	AIO	Layer	`AIO:ELULayer`	Imported
Embedding Layer A layer that turns positive integers (indexes) into dense vectors of fixed size.	AIO	Layer	`AIO:EmbeddingLayer`	Imported
Embodied LLM aka Embodied Large Language Model, multimodal grounding A large language model that integrates language with other modalities like vision audio and robotics to enable grounded language understandi…	AIO	Model	`AIO:EmbodiedLLM`	Imported
Emergent Bias A use and interpretation bias resulting from the use and reliance on algorithms across new or unanticipated contexts.	AIO	Bias	`AIO:EmergentBias`	Imported
Encoder LLM A large language model that uses an encoder-only architecture to encode the input sequence into a fixed-length representation which is then…	AIO	Model	`AIO:EncoderLLM`	Imported
Encoder-Decoder LLM A large language model introduced in the "Attention Is All You Need" paper. The encoder processes the input sequence to generate a hidden re…	AIO	Model	`AIO:EncoderDecoderLLM`	Imported
End-to-End Memory Network aka MemN2N, End-to-End Memory Networks A neural architecture that answers a query through one or more differentiable soft-attention reads over separately embedded input and output…	Curated	Architectures	`AIMech:EndToEndMemoryNetwork`	6 claims 1 source
Energy-Based LLM aka Energy-Based Large Language Model, energy scoring… A large language model which models the explicit probability density over token sequences using an energy function, rather than an autoregre…	AIO	Model	`AIO:EnergyBasedLLM`	Imported
Enforced hill climbing A forward state-space search controller that repeatedly uses breadth-first search to find a state with a strictly smaller heuristic value, c…	Curated	Algorithms	`AIMech:EnforcedHillClimbing`	5 claims 1 source
Ensemble Learning A machine learning task focused on methods that use multiple learning algorithms to achieve better predictive performance than any of the co…	AIO	MachineLearningTask	`AIO:EnsembleLearning`	Imported
Entropy Search A Bayesian global optimization algorithm that approximates the location of a function minimum on sampled representer points using expectatio…	Curated	Algorithms	`AIMech:EntropySearch`	6 claims 2 sources
Eppstein–Wang RAND closeness approximation aka Eppstein-Wang closeness approximation A randomized graph-analysis algorithm that estimates closeness centrality from independent uniformly sampled source vertices, averaging scal…	Curated	Algorithms	`AIMech:EppsteinWangRANDClosenessApproximation`	6 claims 1 source
Epsilon-truncation for Conditional Distribution Prediction aka CDP epsilon-truncation A modification of conditional distribution prediction for IDA* tree size that removes conditional child-type probabilities below a calibrate…	Curated	Algorithms	`AIMech:EpsilonTruncationCDP`	5 claims 1 source
Equal opportunity in binary classification aka Equal opportunity (true-positive parity), Equality of opportunity (true-positive parity) A binary-classification fairness criterion requiring equal probabilities of a positive prediction across specified protected groups among in…	Curated	Evaluation Criteria	`AIMech:EqualOpportunity`	1 claim 1 source
Equalized odds aka Equalised odds A fairness criterion requiring a predictor's output to be conditionally independent of a specified protected attribute given the target outc…	Curated	Evaluation Criteria	`AIMech:EqualizedOdds`	1 claim 1 source
Equalized-odds postprocessing for binary predictors aka Hardt equalized-odds binary postprocessing A randomized postprocessing algorithm that uses a binary predictor and protected-group membership to minimize expected label loss subject to…	Curated	Algorithms	`AIMech:EqualizedOddsBinaryPostprocessing`	1 claim 1 source
Error Propagation Bias aka Error Propagation A processing bias characterized by the effect of variables' uncertainties (or errors more specifically random errors) on the uncertainty of…	AIO	Bias	`AIO:ErrorPropagationBias`	Imported
Estimation of distribution algorithms A family of population-based optimization algorithms whose central offspring-generation mechanism estimates a search distribution from selec…	Curated	Algorithms	`AIMech:EstimationOfDistributionAlgorithms`	6 claims 3 sources
Ethical LLM aka Ethical Large Language Model, constituitional AI… A large language model that is trained to uphold certain ethical principles values or rules in its language generation to increase safety an…	AIO	Model	`AIO:EthicalLLM`	Imported
Evaluation Bias A selection and sampling bias arising when testing populations do not equally represent user populations or when inappropriate performance m…	AIO	Bias	`AIO:EvaluationBias`	Imported
Evolutionary LLM aka Evolutionary Language Model, evolutionary algorithms… A large language model that applies principles of evolutionary computation to optimize its structure and parameters evolving over time to im…	AIO	Model	`AIO:EvolutionaryLLM`	Imported
Exact PoClustering aka Maximal-clique PoClustering A dissimilarity-based clustering construction that accumulates maximal cliques of pairwise-distance threshold graphs and organizes their set…	Curated	Algorithms	`AIMech:ExactPoClustering`	6 claims 2 sources
Exclusion Bias A selection and sampling bias occurring when specific groups of user populations are excluded from testing and analysis.	AIO	Bias	`AIO:ExclusionBias`	Imported
Exemplar-Based Convex Clustering aka Convex Clustering with Exemplar-Based Models, Convex Mixture Model Clustering An exemplar-based clustering procedure that fixes candidate component centers at every observed point, fits their simplex weights through a…	Curated	Algorithms	`AIMech:ExemplarBasedConvexClustering`	5 claims 1 source
Expectation Conditional Maximization aka ECM Algorithm, ECM An extension of expectation maximization that replaces a joint maximization of the expected complete-data log likelihood with a sequence of…	Curated	Algorithms	`AIMech:ExpectationConditionalMaximization`	3 claims 1 source
Expectation Conditional Maximization Either aka ECME Algorithm, ECME An extension of expectation conditional maximization that replaces selected final conditional maximizations of expected complete-data log li…	Curated	Algorithms	`AIMech:ExpectationConditionalMaximizationEither`	3 claims 2 sources
Expectation maximization aka EM Parameter estimation alternating expected complete-data log-likelihood evaluation and its maximization.	Curated	Algorithms	`AIMech:ExpectationMaximization`	1 claim 1 source
Expected improvement acquisition An acquisition criterion for deterministic scalar minimization that scores a candidate evaluation by the predictive expected positive reduct…	Curated	Mathematical Methods	`AIMech:ExpectedImprovementAcquisition`	5 claims 1 source
Explainable LLM aka Explainable Language Model, XAI LLM… A large language model that is designed to provide insights into its decision-making process making it easier for users to understand and tr…	AIO	Model	`AIO:ExplainableLLM`	Imported
Exponential Function A mathematical function denoted by f(x)=exp or e^{x}.	AIO	MathematicalFunction	`AIO:ExponentialFunction`	Imported
Exponential generalized root model aka Exponential GRM A generalized root probability model on nonnegative continuous variables with exponential base measure and symmetric root-product interactio…	Curated	Model Families	`AIMech:ExponentialGeneralizedRootModel`	1 claim 1 source
Exponential natural evolution strategies A Gaussian black-box optimization algorithm that adapts a search mean and full covariance factor from ranked samples in local standard-norma…	Curated	Algorithms	`AIMech:ExponentialNaturalEvolutionStrategies`	6 claims 1 source
Exponential Smoothing State Space Model aka ETS A model that combines exponential smoothing with state space modeling, allowing for the inclusion of both trend and seasonal components. Use…	AIO	Model	`AIO:ExponentialSmoothingStateSpaceModel`	Imported
Exponential square root graphical model aka Exponential SQR, Exponential square root Markov random field A graphical probability model on nonnegative continuous variables with unary square-root terms and symmetric products of square roots, deriv…	Curated	Model Families	`AIMech:ExponentialSquareRootGraphicalModel`	1 claim 2 sources
Exponential-family harmonium aka EFH A bipartite undirected model family coupling visible and hidden exponential-family sufficient statistics through bilinear interactions, with…	Curated	Model Families	`AIMech:ExponentialFamilyHarmonium`	3 claims 1 source
Exponentiated-gradient reduction for fair classification aka Agarwal exponentiated-gradient fairness reduction A cost-sensitive classification reduction that alternates classifier best responses with exponentiated-gradient updates of bounded Lagrange…	Curated	Algorithms	`AIMech:ExponentiatedGradientFairClassification`	1 claim 1 source
Extended Guided Local Search aka EGLS The Tsang–Mills–Ford extension of Guided Local Search that combines cost-scaled penalty weighting, aspiration for a new best original-object…	Curated	Algorithms	`AIMech:ExtendedGuidedLocalSearch`	1 claim 1 source
Extreme Learning Machine aka ELM A feedback network with randomly assigned hidden nodes that are not updated during training.	AIO	Network	`AIO:ExtremeLearningMachine`	Imported
F-Race A statistical racing method for configuring metaheuristics that evaluates a finite candidate set on shared problem-instance blocks and elimi…	Curated	Algorithms	`AIMech:FRace`	1 claim 1 source
FABOLAS aka Fast Bayesian Optimization on Large Data Sets A Bayesian hyperparameter optimization algorithm that jointly chooses a model configuration and training-data subset size using surrogate mo…	Curated	Algorithms	`AIMech:FABOLAS`	2 claims 5 sources
Factored Language Model aka Factorized Language Model A language model that views each word as a vector of multiple factors such as part-of-speech morphology and semantics to improve language mo…	AIO	Model	`AIO:FactoredLanguageModel`	Imported
Factored restricted Boltzmann machine language model aka FRBM A conditional neural word model that factorizes position-specific word-to-hidden weights through a shared word-embedding matrix and couples…	Curated	Architectures	`AIMech:FactoredRestrictedBoltzmannMachineLanguageModel`	1 claim 1 source
Factorial hidden Markov model aka FHMM, Factorial HMM A directed latent sequence-model family in which several independently evolving hidden Markov chains jointly determine the observation distr…	Curated	Model Families	`AIMech:FactorialHiddenMarkovModel`	1 claim 1 source
Factorized LHUC Adaptation An acoustic-model adaptation procedure that combines separately estimated speaker and environment LHUC transforms by interpolating their tra…	Curated	Algorithms	`AIMech:FactorizedLHUCAdaptation`	5 claims 1 source
Factorized LLM aka Factorized Large Language Model, Factorized Learning Assisted with Large Language Model… A large language model that decomposes the full language modeling task into multiple sub-components or experts that each focus on a subset o…	AIO	Model	`AIO:FactorizedLLM`	Imported
Factorized variational sparse-spectrum Gaussian-process inference aka fVSSGP The Gal–Turner finite spectral regression inference procedure that explicitly optimizes diagonal Gaussian output-coefficient factors and ind…	Curated	Algorithms	`AIMech:FactorizedVariationalSparseSpectrumGaussianProcessInference`	5 claims 3 sources
FAIRLEARNING aka Kusner counterfactual fair learning A causal-model-dependent learning procedure that minimizes predictive loss averaged over inferred background variables, restricting the late…	Curated	Algorithms	`AIMech:FairLearning`	1 claim 1 source
Fairness LP aka Dwork fairness linear program A finite-population optimization procedure that assigns outcome distributions to individuals to minimize expected loss under pairwise Lipsch…	Curated	Algorithms	`AIMech:FairnessLP`	1 claim 1 source
Family-of-harmonium aka FoH A classification model family comprising separately parameterized harmoniums for each class, with binary text features and Gaussian image fe…	Curated	Model Families	`AIMech:FamilyOfHarmonium`	3 claims 1 source
Fast AutoAugment aka FAA An augmentation-policy search procedure that evaluates candidate transformations on held-out training examples using a fixed classifier trai…	Curated	Algorithms	`AIMech:FastAutoAugment`	2 claims 5 sources
Fast condensed prototype-based domain description aka FastCPDD, FCPDD A heuristic for selecting PDD prototypes that samples remaining reference observations, computes their radius offsets against the full datas…	Curated	Algorithms	`AIMech:FastCondensedPrototypeBasedDomainDescription`	5 claims 1 source
Fast Dropout Training aka Fast dropout A dropout approximation procedure that replaces masked weighted sums by Gaussian distributions with matched means and variances, using Gauss…	Curated	Algorithms	`AIMech:FastDropoutTraining`	5 claims 2 sources
Fast Global Kernel K-Means An incremental kernel clustering algorithm that chooses each new singleton seed by maximizing a computable lower bound on error reduction, t…	Curated	Algorithms	`AIMech:FastGlobalKernelKMeans`	4 claims 1 source
Fast Local Search aka FLS A neighborhood-search procedure that uses activation bits to scan selected subneighborhoods, deactivating unsuccessful ones and reactivating…	Curated	Algorithms	`AIMech:FastLocalSearch`	1 claim 2 sources
Fast persistent contrastive divergence aka FPCD A persistent-chain RBM learning algorithm that adds rapidly updated, rapidly decaying auxiliary parameters to the sampling energy while reta…	Curated	Algorithms	`AIMech:FastPersistentContrastiveDivergence`	1 claim 1 source
FastICA aka Fast Independent Component Analysis A family of independent-component estimation algorithms that repeatedly apply normalized approximate-Newton fixed-point updates to nonlinear…	Curated	Algorithms	`AIMech:FastICA`	4 claims 2 sources
Feature Extraction aka Attribute Extraction, Feature Isolation… A data enhancement that transforms raw data into a set of measurable characteristics that can be used as input for machine learning algorith…	AIO	Preprocessing	`AIO:FeatureExtraction`	Imported
Feature-wise Linear Modulation aka FiLM A neural conditioning layer that applies a feature-wise affine transformation whose scale and shift are generated from conditioning informat…	Curated	Layers & Modules	`AIMech:FeatureWiseLinearModulation`	5 claims 1 source
Federated Learning A deep neural network trained across decentralized edge devices or servers holding local data samples without exchanging them.	AIO	Network	`AIO:FederatedLearning`	Imported
Federated LLM aka Federated Large Language Model, decentralized training… A large language model that is trained in a decentralized manner across multiple devices or silos without directly sharing private data enab…	AIO	Model	`AIO:FederatedLLM`	Imported
Feedback Loop Bias A use and interpretation bias occurring when an algorithm learns from user behavior and feeds that behavior back into the model.	AIO	Bias	`AIO:FeedbackLoopBias`	Imported
Feedback Network aka FBN An artificial neural network that refines its representations iteratively based on feedback from previous outputs.	AIO	Network	`AIO:FeedbackNetwork`	Imported
Fill algorithm An idealized finite constraint-satisfaction search algorithm that takes any strictly cost-reducing single-variable change when available and…	Curated	Algorithms	`AIMech:FillAlgorithm`	1 claim 1 source
FiLM Parameter-Arithmetic Inference A post-training visual-question-answering procedure that uses a parser to construct related questions and combines their generated FiLM scal…	Curated	Algorithms	`AIMech:FiLMParameterArithmeticInference`	5 claims 1 source
First-come, first-served beam decoding aka FCFS beam decoding The sequence beam-decoding procedure described by Kasai and colleagues that stores completed hypotheses separately from the continuing beam…	Curated	Algorithms	`AIMech:FCFSBeamDecoding`	2 claims 2 sources
Fixed Effects Model aka FEM A regression analysis in which the model parameters are fixed or non-random quantities.	AIO	MachineLearningTask	`AIO:FixedEffectsModel`	Imported
Fixed-Component Mixture-Weight EM aka Mixture-Weight Expectation Maximization An expectation-maximization specialization that keeps every component distribution fixed and updates only their simplex mixing weights by av…	Curated	Algorithms	`AIMech:FixedComponentMixtureWeightEM`	3 claims 1 source
Fixed-length Poisson Markov random field aka LPMRF, Fixed-length Poisson MRF A finite-total count distribution whose probability on nonnegative integer vectors summing to a specified total is proportional to a Poisson…	Curated	Model Families	`AIMech:FixedLengthPoissonMarkovRandomField`	1 claim 2 sources
Fixed-length Poisson MRF topic model aka LPMRF topic model A probabilistic topic model that allocates a document total among topics, draws an independent fixed-length Poisson-MRF count vector for eac…	Curated	Model Families	`AIMech:FixedLengthPoissonMRFTopicModel`	1 claim 2 sources
FixMatch A semi-supervised classifier-training procedure that fits labeled examples and trains on strongly augmented unlabeled inputs using hard pseu…	Curated	Algorithms	`AIMech:FixMatch`	2 claims 3 sources
Flake exact-flow community identification aka EXACT-FLOW-COMMUNITY, Flake exact-flow community algorithm A seeded web-graph grouping procedure that adds infinite-capacity source arcs to seed vertices, makes original hyperlink connections bidirec…	Curated	Algorithms	`AIMech:FlakeExactFlowCommunity`	6 claims 2 sources
Flake focused community crawling aka APPROXIMATE-FLOW-COMMUNITY, Flake focused-crawl algorithm A flow-based focused-crawling family that alternates gathering a local web graph around positive seed pages, extracting a group through seed…	Curated	Algorithms	`AIMech:FlakeFocusedCrawl`	7 claims 2 sources
FlashAttention An exact attention computation algorithm using tiling and recomputation to reduce transfers between GPU memory levels.	Curated	Algorithms	`AIMech:FlashAttention`	1 claim 1 source
FlashConv An execution algorithm for state-space sequence convolutions that fuses FFT-based convolution in GPU on-chip memory, uses block FFT matrix m…	Curated	Algorithms	`AIMech:FlashConv`	1 claim 1 source
Flatten Layer A reshaping layer that flattens the input	AIO	Layer	`AIO:FlattenLayer`	Imported
Flattened slice sampling A finite categorical conditional-update algorithm that splits excess probability from a maximum-probability state into additional bars and s…	Curated	Algorithms	`AIMech:FlattenedSliceSampling`	6 claims 1 source
Flow matching aka FM (flow matching) A generative-model training method that fits a time-dependent vector field by regression to velocities associated with a chosen probability…	Curated	Algorithms	`AIMech:FlowMatching`	1 claim 1 source
FocusedILS A ParamILS algorithm-configuration method that adaptively extends paired evaluation prefixes until one configuration dominates the other, an…	Curated	Algorithms	`AIMech:FocusedILS`	1 claim 1 source
FractalNet DropPath A structured regularization procedure for fractal networks that trains shared parameters using locally selected nonempty subsets of join inp…	Curated	Algorithms	`AIMech:FractalNetDropPath`	6 claims 1 source
FractionalMaxPool2D Layer aka FractionalMaxPool2D A pooling layer that applies a 2D fractional max pooling over an input signal composed of several input planes.	AIO	Layer	`AIO:FractionalMaxPool2DLayer`	Imported
FractionalMaxPool3D Layer aka FractionalMaxPool3D A pooling layer that applies a 3D fractional max pooling over an input signal composed of several input planes.	AIO	Layer	`AIO:FractionalMaxPool3DLayer`	Imported
Full-echo Q-routing An information-exploration modification of tabular Q-routing that queries immediate neighbors whenever a node needs a routing decision and u…	Curated	Algorithms	`AIMech:FullEchoQRouting`	4 claims 1 source
Fully adaptive cross-entropy optimization A named cross-entropy optimization variant, called FACE in the source, that fixes an elite sample count and adapts the number of sampled can…	Curated	Algorithms	`AIMech:FullyAdaptiveCrossEntropyOptimization`	6 claims 1 source
Fully factorized mean-field inference aka Naive mean-field inference, Fully factorized variational inference A variational inference method that restricts its approximating distribution to a product of single-variable factors and adjusts those facto…	Curated	Mathematical Methods	`AIMech:FullyFactorizedMeanFieldInference`	1 claim 1 source
Fully visible sigmoid belief network aka FVSBN, Logistic autoregressive Bayesian network A fully observed binary autoregressive probabilistic model whose conditional probability at each position is a logistic function of a bias a…	Curated	Architectures	`AIMech:FullyVisibleSigmoidBeliefNetwork`	1 claim 3 sources
Funding Bias A group bias arising when biased results are reported to support or satisfy the funding agency or financial supporter of a research study.	AIO	Bias	`AIO:FundingBias`	Imported
Gamma filter aka Adaptive gamma filter, ADALINE(μ) A linear adaptive filter family that combines a direct input tap with weighted cascaded first-order gamma-memory traces, using one shared me…	Curated	Model Families	`AIMech:GammaFilter`	6 claims 1 source
Gamma neural model aka Gamma neural network, Gamma net… A neural architecture family that represents delayed inputs or neural outputs by weighted gamma-kernel memory traces, realized through casca…	Curated	Architectures	`AIMech:GammaNeuralModel`	6 claims 2 sources
Gated Graph Neural Network aka GG-NN, Gated Graph Neural Networks A graph neural architecture that initializes node states from annotations, repeatedly combines edge-type- and direction-specific neighbor me…	Curated	Architectures	`AIMech:GatedGraphNeuralNetwork`	6 claims 1 source
Gated Graph Sequence Neural Network aka GGS-NN, Gated Graph Sequence Neural Networks A graph-to-sequence neural architecture that repeatedly runs gated graph propagation to predict an output and update node annotations, using…	Curated	Architectures	`AIMech:GatedGraphSequenceNeuralNetwork`	6 claims 1 source
Gated Recurrent Unit aka GRU A long short-term memory network that is a gating mechanism in recurrent neural networks similar to LSTMs but with fewer parameters and no o…	AIO	Network	`AIO:GatedRecurrentUnit`	Imported
Gated-feedback recurrent neural network aka GF-RNN A layered recurrent architecture in which learned input-dependent scalar gates modulate recurrent projections from every previous layer stat…	Curated	Architectures	`AIMech:GatedFeedbackRecurrentNeuralNetwork`	6 claims 1 source
Gaussian Differentiable Pooling A spatial pooling and unpooling component whose nonnegative, unit-L2 weights are square-root normalized axis-aligned Gaussian samples, with…	Curated	Layers & Modules	`AIMech:GaussianDifferentiablePooling`	5 claims 1 source
Gaussian Factor Analysis aka Linear Gaussian Factor Analysis A linear Gaussian latent-variable model in which observed variables share a lower-dimensional Gaussian factor and have conditionally indepen…	Curated	Model Families	`AIMech:GaussianFactorAnalysis`	4 claims 1 source
Gaussian loss-smoothed mixed-model variational inference aka NCVB-UF A nonconjugate variational inference procedure for a loss-defined mixed-effects generalized posterior that retains a joint Gaussian over fix…	Curated	Algorithms	`AIMech:GaussianLossSmoothedMixedModelVariationalInference`	7 claims 2 sources
Gaussian message conflict diagnostic A Bayesian GLMM screening procedure that separates Gaussian prior and likelihood natural-parameter messages at local variational fixed point…	Curated	Algorithms	`AIMech:GaussianMessageConflictDiagnostic`	7 claims 3 sources
Gaussian process regression aka GPR Probabilistic regression conditioning a Gaussian-process prior on observed training data.	Curated	Model Families	`AIMech:GaussianProcessRegression`	1 claim 1 source
Gaussian-process moment matching for Gaussian inputs aka Gaussian input Gaussian process moment matching A Gaussian-process prediction procedure that analytically integrates a fixed squared-exponential posterior over an independently prescribed…	Curated	Algorithms	`AIMech:GaussianProcessGaussianInputMomentMatching`	5 claims 3 sources
GaussianDropout Layer A regularization layer that applies multiplicative 1-centered Gaussian noise.	AIO	Layer	`AIO:GaussianDropoutLayer`	Imported
GaussianNoise Layer A regularization layer that applies additive zero-centered Gaussian noise.	AIO	Layer	`AIO:GaussianNoiseLayer`	Imported
GELU Function aka GELU, Gaussian Error Linear Unit A mathematical function that computes x * P(X <= x) where P(X) ~ N(0 1) weighting inputs by their value rather than gating inputs by their s…	AIO	MathematicalFunction	`AIO:GELUFunction`	Imported
Generalized advantage estimation aka GAE An advantage-function estimator for policy-gradient learning formed from an exponentially weighted sum of temporal-difference residuals.	Curated	Mathematical Methods	`AIMech:GeneralizedAdvantageEstimation`	1 claim 1 source
Generalized Alternating Minimization aka GAM (generalized alternating minimization) An information-geometric fitting framework that updates a generating distribution constrained by the observations and model parameters to de…	Curated	Algorithms	`AIMech:GeneralizedAlternatingMinimization`	4 claims 1 source
Generalized Autoregressive Conditional Heteroskedasticity aka GARCH A model that incorporates lagged conditional variances, allowing for more flexibility in modeling time-varying volatility.	AIO	Model	`AIO:GeneralizedAutoregressiveConditionalHeteroskedasticity`	Imported
Generalized component analysis aka GCA An undirected latent-component model family coupling categorical text and heterogeneous document attributes to positive lognormal hidden var…	Curated	Model Families	`AIMech:GeneralizedComponentAnalysis`	3 claims 1 source
Generalized core vector machine aka Generalized CVM, Generalized core vector machines A kernel optimization algorithm that converts a quadratic program with a positive-semidefinite Gram matrix and simplex constraints into a ce…	Curated	Algorithms	`AIMech:GeneralizedCoreVectorMachine`	5 claims 2 sources
Generalized Expectation Maximization aka Generalized EM, GEM (generalized expectation maximization) A latent-variable likelihood-fitting framework that computes the expected complete-data log likelihood under the current exact posterior and…	Curated	Algorithms	`AIMech:GeneralizedExpectationMaximization`	3 claims 2 sources
Generalized Few-shot Learning aka GFSL A deep neural network that learns novel classes from few samples per class, preventing catastrophic forgetting of base classes and ensuring…	AIO	Network	`AIO:GeneralizedFewshotLearning`	Imported
Generalized Linear Model aka GLM A regression analysis that relates the linear model to the response variable via a link function and allowing the variance of each measureme…	AIO	MachineLearningTask	`AIO:GeneralizedLinearModel`	Imported
Generalized root model aka Generalized root graphical model A family of finite undirected probability models that retains univariate exponential-family base measures and couples coordinatewise roots o…	Curated	Model Families	`AIMech:GeneralizedRootModel`	1 claim 1 source
Generative Adversarial Network aka GAN An unsupervised pretrained network framework where two neural networks contest in a game to generate new data with the same statistics as th…	AIO	Network	`AIO:GenerativeAdversarialNetwork`	Imported
Generative Adversarial Network-Augmented LLM aka GAN-Large Language Model, Generative Adversarial Network-Augmented Large Language Model… A large language model which incorporates a generative adversarial network (GAN) into its training process, using a discriminator network to…	AIO	Model	`AIO:GenerativeAdversarialNetworkAugmentedLLM`	Imported
Generative Commonsense LLM aka Generative Commonsense Large Language Model, World Model… A large language model that is trained to understand and model basic physics causality and common sense about how the real world works.	AIO	Model	`AIO:GenerativeCommonsenseLLM`	Imported
Generative Language Interface aka Interactive generation A language model that enables users to engage in an interactive dialogue with an LLM providing feedback to guide and refine the generated ou…	AIO	Model	`AIO:GenerativeLanguageInterface`	Imported
Generative Topographic Mapping aka GTM A nonlinear latent-variable density model with a uniform discrete prior on fixed latent grid nodes, mapped through a shared smooth function…	Curated	Model Families	`AIMech:GenerativeTopographicMapping`	4 claims 1 source
Generic lazy-neighbor agglomerative clustering aka Generic linkage algorithm (Müllner), GENERIC_LINKAGE An agglomerative clustering algorithm that caches candidate nearest neighbors and lower bounds on row-minimum dissimilarities in a priority…	Curated	Algorithms	`AIMech:GenericLazyNeighborAgglomerativeClustering`	6 claims 3 sources
Generic tree sampling aka Chen generic sampling, Generic importance-weighted tree sampling An importance-sampling generalization of Chen heuristic tree sampling that merges representatives of ordered tree strata using specified pos…	Curated	Algorithms	`AIMech:GenericTreeSampling`	5 claims 1 source
GENET A connectionist architecture for finite constraint satisfaction that represents variable assignments by active label nodes and alternates in…	Curated	Architectures	`AIMech:GENET`	1 claim 1 source
Genetic algorithm aka GA Evolutionary optimization using fitness-based selection and genetic variation of candidate solutions.	Curated	Algorithms	`AIMech:GeneticAlgorithm`	1 claim 1 source
Genie clustering aka Genie linkage, Genie hierarchical clustering An agglomerative clustering algorithm that normally selects a nearest pair by single-link distance and, when cluster-size inequality exceeds…	Curated	Algorithms	`AIMech:GenieClustering`	6 claims 4 sources
Gibbs sampling aka Gibbs sampler A Markov chain Monte Carlo algorithm that repeatedly draws a coordinate or block from its full conditional distribution given the current va…	Curated	Algorithms	`AIMech:GibbsSampling`	2 claims 2 sources
Girvan–Newman community detection aka Girvan–Newman algorithm, edge-betweenness community detection A divisive community-detection algorithm that repeatedly removes an edge with maximal current shortest-path betweenness and recalculates aff…	Curated	Algorithms	`AIMech:GirvanNewmanCommunityDetection`	6 claims 1 source
Global Kernel K-Means An incremental kernel clustering algorithm that adds a singleton datum cluster at each stage, runs kernel k-means from each such candidate p…	Curated	Algorithms	`AIMech:GlobalKernelKMeans`	4 claims 1 source
Global Kernel K-Means with Convex Mixture Models aka CMM-Initialized Global Kernel K-Means An incremental kernel clustering algorithm that fits a convex mixture over datum exemplars once, restricts each new-cluster seed search to i…	Curated	Algorithms	`AIMech:ConvexMixtureInitializedGlobalKernelKMeans`	5 claims 1 source
GlobalAveragePooling1D Layer aka GlobalAvgPool1D A pooling layer that performs global average pooling operation for temporal data.	AIO	Layer	`AIO:GlobalAveragePooling1DLayer`	Imported
GlobalAveragePooling2D Layer aka GlobalAvgPool2D A pooling layer that performs global average pooling operation for spatial data.	AIO	Layer	`AIO:GlobalAveragePooling2DLayer`	Imported
GlobalAveragePooling3D Layer aka GlobalAvgPool3D A pooling layer that performs global average pooling operation for 3D data.	AIO	Layer	`AIO:GlobalAveragePooling3DLayer`	Imported
GlobalMaxPooling1D Layer aka GlobalMaxPool1D A pooling layer that performs global max pooling operation for temporal data.	AIO	Layer	`AIO:GlobalMaxPooling1DLayer`	Imported
GlobalMaxPooling2D Layer aka GlobalMaxPool2D A pooling layer that performs global max pooling operation for spatial data.	AIO	Layer	`AIO:GlobalMaxPooling2DLayer`	Imported
GlobalMaxPooling3D Layer aka GlobalMaxPool3D A pooling layer that performs global max pooling operation for 3D data.	AIO	Layer	`AIO:GlobalMaxPooling3DLayer`	Imported
GloVe aka Global Vectors for Word Representation Word-vector learning from global word co-occurrence statistics.	Curated	Algorithms	`AIMech:GloVe`	1 claim 1 source
Gradient boosting machine aka Gradient boosting, GBM Boosting that adds predictors fitted to negative loss-function gradients.	Curated	Algorithms	`AIMech:GradientBoosting`	1 claim 1 source
Gradient norm clipping aka Global gradient norm clipping A gradient transformation that bounds the Euclidean norm of a chosen joint parameter-gradient vector by uniformly scaling it down to a posit…	Curated	Algorithms	`AIMech:GradientNormClipping`	7 claims 3 sources
Gradient-weighted class activation mapping aka Grad-CAM A convolutional-network localization method weighting activation maps by spatially averaged gradients of a selected target output.	Curated	Algorithms	`AIMech:GradCAM`	1 claim 1 source
Graph attention network aka GAT A graph neural architecture that updates node representations using learned attention weights over graph neighborhoods.	Curated	Architectures	`AIMech:GraphAttentionNetwork`	1 claim 1 source
Graph attention network v2 aka GATv2 A graph neural architecture whose neighborhood attention scorer applies a learned scalar projection after a nonlinear transformation of the…	Curated	Architectures	`AIMech:GATv2`	1 claim 1 source
Graph Convolutional Network aka GCN A deep neural network that operates directly on graph structures utilizing structural information.	AIO	Network	`AIO:GraphConvolutionalNetwork`	Imported
Graph Convolutional Policy Network aka GPCN A graph convolutional network that generates goal-directed graphs using reinforcement learning and optimizing for rewards and adversarial lo…	AIO	Network	`AIO:GraphConvolutionalPolicyNetwork`	Imported
Graph degree linkage aka GDL, Graph degree linkage clustering An agglomerative clustering algorithm that merges the pair with greatest symmetric graph-degree affinity, formed by summing products of clus…	Curated	Algorithms	`AIMech:GraphDegreeLinkage`	1 claim 1 source
Graph isomorphism network aka GIN A graph neural architecture using multilayer perceptrons on sums of neighboring representations and a separately weighted self-representatio…	Curated	Architectures	`AIMech:GraphIsomorphismNetwork`	1 claim 1 source
Graph Language Model aka Graph LM, Structured representations A language model that operates over structured inputs or outputs represented as graphs enabling reasoning over explicit relational knowledge…	AIO	Model	`AIO:GraphLanguageModel`	Imported
GraphSAGE An inductive graph representation architecture that learns neighborhood aggregation functions to generate node embeddings from features.	Curated	Architectures	`AIMech:GraphSAGE`	1 claim 1 source
Greedy best-first search aka GBFS A best-first search algorithm that prioritizes open nodes by a heuristic estimate of remaining cost to a goal, without adding the cost alrea…	Curated	Algorithms	`AIMech:GreedyBestFirstSearch`	2 claims 2 sources
Grid Long Short-Term Memory aka Grid LSTM A neural architecture family whose grid blocks couple hidden representations across computational dimensions while maintaining separate gate…	Curated	Architectures	`AIMech:GridLongShortTermMemory`	6 claims 1 source
Grid Search for Hyperparameter Optimization aka Cartesian Hyperparameter Grid Search A hyperparameter optimization procedure that evaluates a finite Cartesian product of chosen values for each configuration variable and selec…	Curated	Algorithms	`AIMech:GridSearchHyperparameterOptimization`	1 claim 1 source
Grid-search reduction for fair classification aka Agarwal grid-search fairness reduction A fairness-aware classification reduction that evaluates cost-sensitive classifier best responses over a grid of Lagrange-multiplier-derived…	Curated	Algorithms	`AIMech:GridSearchFairClassification`	1 claim 1 source
GRINCH clustering aka Grinch algorithm An incremental hierarchical clustering algorithm that uses set-wise linkage scores to revise a binary cluster tree through local rotations,…	Curated	Algorithms	`AIMech:GRINCHClustering`	6 claims 5 sources
Group Bias aka In-group Favoritism, In-group bias… A systemic bias characterized by favoring members of one's in-group over out-group members expressed in evaluation resource allocation and o…	AIO	Bias	`AIO:GroupBias`	Imported
Group-topic model aka GT model A probabilistic model family jointly assigning topics to relation-bearing events and topic-specific latent groups to entities, using event t…	Curated	Model Families	`AIMech:GroupTopicModel`	3 claims 1 source
GroupNorm Layer aka GroupNorm A normalization layer that applies Group Normalization over a mini-batch of inputs.	AIO	Layer	`AIO:GroupNormLayer`	Imported
Groupthink Bias aka Groupthink A group bias in which people in a group make non-optimal decisions due to a desire to conform or fear of dissent.	AIO	Bias	`AIO:GroupthinkBias`	Imported
GRU Layer A recurrent layer that implements the Gated Recurrent Unit architecture.	AIO	Layer	`AIO:GRULayer`	Imported
GRUCell Layer A layer that processes one step within the whole time sequence input for a GRU layer.	AIO	Layer	`AIO:GRUCellLayer`	Imported
GSAT A randomized local-search SAT procedure that repeatedly flips a Boolean variable giving the largest change toward more satisfied CNF clauses…	Curated	Algorithms	`AIMech:GSAT`	1 claim 1 source
GSAT averaging-in strategy A GSAT restart-initialization strategy that reuses agreements between earlier complete assignments, randomizes their differing positions, an…	Curated	Algorithms	`AIMech:GSATAveragingIn`	1 claim 1 source
GSAT clause-weighting strategy A GSAT extension that starts each clause with weight one, uses weighted clause counts to select flips, and increases the weights of clauses…	Curated	Algorithms	`AIMech:GSATClauseWeighting`	1 claim 1 source
GSAT with random noise A GSAT variant that mixes a random flip drawn from all formula variables with a globally best GSAT flip, without restricting the random choi…	Curated	Algorithms	`AIMech:GSATWithRandomNoise`	1 claim 1 source
GSAT with random walk aka GWSAT A GSAT variant that mixes a uniformly chosen flip from the distinct variables currently occurring in unsatisfied clauses with a globally bes…	Curated	Algorithms	`AIMech:GSATWithRandomWalk`	2 claims 3 sources
Guarded discrete stochastic network A binary neural constraint-satisfaction architecture whose main assignment neurons are asymmetrically coupled to empty-row guards and update…	Curated	Architectures	`AIMech:GuardedDiscreteStochasticNetwork`	5 claims 2 sources
Guided Fast Local Search A local-search algorithm that combines GLS feature-penalty updates with FLS activation-bit search, reactivating subneighborhoods associated…	Curated	Algorithms	`AIMech:GuidedFastLocalSearch`	5 claims 2 sources
Guided Genetic Algorithm aka GGA The Lau–Tsang genetic-search framework that uses shared adaptive solution-feature penalties both to modify fitness and to construct per-chro…	Curated	Algorithms	`AIMech:GuidedGeneticAlgorithm`	1 claim 2 sources
Guided Grad-CAM A visualization method combining an upsampled Grad-CAM localization map with guided-backpropagation input-space scores.	Curated	Algorithms	`AIMech:GuidedGradCAM`	1 claim 1 source
Guided local search aka GLS A local-search metaheuristic that repeatedly minimizes an objective augmented by feature penalties, increasing selected penalties at local m…	Curated	Algorithms	`AIMech:GuidedLocalSearch`	1 claim 1 source
Gumbel-Softmax relaxation aka Gumbel-Softmax, Concrete distribution… A continuous relaxation of a finite categorical random variable obtained by applying softmax to independent Gumbel-perturbed log weights div…	Curated	Mathematical Methods	`AIMech:GumbelSoftmaxRelaxation`	3 claims 2 sources
Gumbel-Top-k trick aka Gumbel top-k sampling A categorical sampling construction that adds independent standard Gumbel noise to each category’s log weight and returns the indices of the…	Curated	Mathematical Methods	`AIMech:GumbelTopKTrick`	2 claims 2 sources
Gustafson guided-walk Metropolis sampler A continuous-state Metropolis sampler that augments a univariate state with a binary direction, proposes a half-normal displacement along th…	Curated	Algorithms	`AIMech:GustafsonGuidedWalkMetropolis`	5 claims 1 source
HAC-E network clustering aka HAC-E A hierarchical network-clustering variant that greedily guides agglomeration by the observed edge density between two vertex groups and uses…	Curated	Algorithms	`AIMech:HACE`	4 claims 1 source
HAC-ES network clustering aka HAC-ES A hierarchical network-clustering variant that guides agglomeration by the sum of cross-group edge density and Jaccard overlap of the groups…	Curated	Algorithms	`AIMech:HACES`	5 claims 1 source
HAC-ML network clustering aka HAC-ML A greedy network-clustering algorithm that builds a hierarchical stochastic block structure by merging groups with the least loss of profile…	Curated	Algorithms	`AIMech:HACML`	6 claims 1 source
HAC-Q network clustering aka HAC-Q A hierarchical network-clustering variant that uses a degree-corrected modularity contribution to guide group merges and retains hierarchica…	Curated	Algorithms	`AIMech:HACQ`	5 claims 1 source
Hamiltonian Monte Carlo aka HMC, Hybrid Monte Carlo A Markov chain Monte Carlo algorithm for differentiable continuous targets that augments positions with momenta, proposes a state through re…	Curated	Algorithms	`AIMech:HamiltonianMonteCarlo`	2 claims 2 sources
Hammerstein model A real-valued, single-input single-output, discrete-time deterministic nonlinear dynamical model family formed by a memoryless static nonlin…	Curated	Model Families	`AIMech:HammersteinModel`	4 claims 1 source
Hammerstein–Wiener model A real-valued, single-input single-output, discrete-time deterministic dynamical model family formed by a memoryless static input function,…	Curated	Model Families	`AIMech:HammersteinWienerModel`	4 claims 1 source
Hard Sigmoid Function A mathematical function that is a faster approximation of the sigmoid activation using a piecewise linear approximation.	AIO	MathematicalFunction	`AIO:HardSigmoidFunction`	Imported
HashCRBM A conditional RBM training and prediction method that uses spectral hashing of inputs to retrieve distinct training-output configurations an…	Curated	Algorithms	`AIMech:HashCRBM`	1 claim 2 sources
Hashing Layer A categorical features preprocessing layer which hashes and bins categorical features.	AIO	Layer	`AIO:HashingLayer`	Imported
HDBSCAN aka Hierarchical DBSCAN Hierarchical density-based clustering that selects clusters across density scales.	Curated	Algorithms	`AIMech:HDBSCAN`	1 claim 1 source
Helmholtz machine A hierarchical probabilistic neural model that pairs a top-down generative model with a separately parameterized bottom-up recognition model…	Curated	Architectures	`AIMech:HelmholtzMachine`	1 claim 2 sources
Heuristic tree sampling aka Chen heuristic sampling A randomized estimator of additive properties of an implicit rooted tree that processes ordered strata using one sampled representative and…	Curated	Algorithms	`AIMech:HeuristicTreeSampling`	5 claims 2 sources
Hidden Layer A layer located between the input and output that performs nonlinear transformations of the inputs entered into the network.	AIO	Layer	`AIO:HiddenLayer`	Imported
Hidden Markov decision tree aka HMDT A conditional latent sequence-model family that extends a probabilistic hierarchical decision tree by coupling each decision level to the sa…	Curated	Model Families	`AIMech:HiddenMarkovDecisionTree`	1 claim 1 source
Hidden Markov model aka HMM A sequence model whose hidden Markov states generate observations through state-dependent emission distributions.	Curated	Model Families	`AIMech:HiddenMarkovModel`	1 claim 1 source
Hidden Markov model with auxiliary memory aka Auxiliary-memory context-sensitive hidden Markov model A hidden-state symbol-sequence model family in which paired states write emitted symbols to auxiliary memory and later read them to conditio…	Curated	Model Families	`AIMech:HiddenMarkovModelWithAuxiliaryMemory`	1 claim 1 source
Hidden Markov random field aka HMRF, Hidden Markov field A latent-variable graphical-model family whose unobserved label field has the Markov property on a specified neighborhood graph, with observ…	Curated	Model Families	`AIMech:HiddenMarkovRandomField`	1 claim 1 source
Hidden Markov tree aka HMT A latent-variable model on a fixed rooted tree in which hidden states factor into a root distribution and conditionally independent parent-t…	Curated	Model Families	`AIMech:HiddenMarkovTree`	1 claim 1 source
Hidden semi-Markov model aka HSMM, Explicit-duration hidden Markov model… A latent-state sequence-model family that assigns explicit distributions to state sojourn durations, with state changes governed by an embed…	Curated	Model Families	`AIMech:HiddenSemiMarkovModel`	1 claim 1 source
Hidden–observed pair Markov random field aka Pairwise hidden–observed Markov field A latent-variable spatial-model family in which each site contains a hidden label and an observation, and their joint paired field has a nor…	Curated	Model Families	`AIMech:HiddenObservedPairMarkovRandomField`	1 claim 1 source
Hierarchical Classification A classification focused on methods that group things according to a hierarchy.	AIO	MachineLearningTask	`AIO:HierarchicalClassification`	Imported
Hierarchical Clustering aka HCL A clustering that builds a hierarchy of clusters.	AIO	MachineLearningTask	`AIO:HierarchicalClustering`	Imported
Hierarchical harmonium aka HH A labeled harmonium model family coupling binary words, Gaussian image features and binary category indicators to shared Gaussian latent var…	Curated	Model Families	`AIMech:HierarchicalHarmonium`	3 claims 1 source
Hierarchical Language Model aka Hierarchical LM, multi-scale representations A language model that represents language at multiple levels of granularity learning hierarchical representations that capture both low-leve…	AIO	Model	`AIO:HierarchicalLanguageModel`	Imported
Hierarchical log-bilinear language model aka HLBL A next-word language architecture that computes one linear context feature vector and uses its dot products with internal-node vectors to as…	Curated	Architectures	`AIMech:HierarchicalLogBilinearLanguageModel`	1 claim 1 source
Hierarchical mixture of experts aka HME A conditional mixture-model family that organizes output experts as leaves of a tree and forms each leaf’s mixture weight by multiplying inp…	Curated	Model Families	`AIMech:HierarchicalMixtureOfExperts`	1 claim 1 source
Hierarchical pachinko allocation model aka hPAM A pachinko topic-model family that associates word-emission distributions with internal topic nodes as well as terminal topics, allowing doc…	Curated	Model Families	`AIMech:HierarchicalPachinkoAllocationModel`	3 claims 1 source
Hierarchical probabilistic neural network language model A neural next-word architecture that factors word probabilities along a binary vocabulary tree and shares a nonlinear branch predictor condi…	Curated	Architectures	`AIMech:HierarchicalProbabilisticNeuralNetworkLanguageModel`	1 claim 1 source
Hierarchical softmax A neural categorical-output component that assigns a probability to each vocabulary leaf by multiplying normalized branch probabilities alon…	Curated	Layers & Modules	`AIMech:HierarchicalSoftmax`	1 claim 3 sources
High-order polynomial projection operators aka HiPPO (polynomial projection) A family of time-dependent operators that represents a signal's past by coefficients of its optimal finite-dimensional polynomial approximat…	Curated	Mathematical Methods	`AIMech:HiPPOProjection`	1 claim 1 source
Hill climbing aka Hill-climbing search, Greedy local search A family of local-improvement search procedures that replaces a current solution with a strictly better neighbor and stops when no improving…	Curated	Algorithms	`AIMech:HillClimbing`	1 claim 2 sources
Historical Bias A bias characterized by long-standing biases encoded in society over time distinct from biases in historical description or interpretation.	AIO	Bias	`AIO:HistoricalBias`	Imported
HITS hub and authority ranking aka HITS A link-analysis ranking algorithm that constructs a query-focused directed page graph and alternately propagates authority scores from incom…	Curated	Algorithms	`AIMech:HITSRanking`	5 claims 1 source
Holland bucket-brigade credit assignment A classifier-system credit-assignment procedure in which satisfied condition/action rules compete using strength-and-specificity bids, winni…	Curated	Algorithms	`AIMech:HollandBucketBrigade`	5 claims 1 source
Hopfield Network aka HN, Ising model of a neural network… A symmetrically connected network that is a type of recurrent artificial neural network serving as a content-addressable memory system.	AIO	Network	`AIO:HopfieldNetwork`	Imported
Hostile Attribution Bias A use and interpretation bias where individuals perceive benign or ambiguous behaviors as hostile.	AIO	Bias	`AIO:HostileAttributionBias`	Imported
HRSAT A source-scoped SAT-search algorithm described by the literal composition of the 1995 GenSAT stages: a probability-controlled choice between…	Curated	Algorithms	`AIMech:HRSAT`	5 claims 2 sources
HSAT A GSAT variant that breaks ties among best-scoring variable flips by choosing the variable flipped least recently in the current attempt, us…	Curated	Algorithms	`AIMech:HSAT`	1 claim 1 source
Human Bias A bias in human thought based on heuristic principles leading to simplified judgmental operations.	AIO	Bias	`AIO:HumanBias`	Imported
Human Reporting Bias An individual bias that arises when users depend on automated systems as heuristic substitutes for their own information-seeking and process…	AIO	Bias	`AIO:HumanReportingBias`	Imported
Hungry Hungry Hippos layer aka H3 A sequence layer that combines projected queries, keys and values with shift and diagonal state-space models, using multiplicative interacti…	Curated	Layers & Modules	`AIMech:H3Layer`	1 claim 1 source
Hyperband A hyperparameter resource-allocation algorithm that runs successive-halving brackets with different initial configuration counts and startin…	Curated	Algorithms	`AIMech:Hyperband`	1 claim 1 source
IA3 Activation Rescaling aka IA3, Infused Adapter by Inhibiting and Amplifying Inner Activations A transformer adaptation method that learns task-specific vectors to rescale attention key/value channels and intermediate feedforward activ…	Curated	Algorithms	`AIMech:IA3ActivationRescaling`	5 claims 2 sources
ID3 aka Iterative Dichotomiser 3 Decision-tree induction that selects categorical attributes by information gain.	Curated	Algorithms	`AIMech:ID3`	1 claim 1 source
IDA* with an Incremental Model aka IDA*IM An iterative-deepening heuristic search algorithm that learns a conditional model of search-tree cost increments, predicts later cost thresh…	Curated	Algorithms	`AIMech:IDAStarIncrementalModel`	5 claims 1 source
Identity-initialized rectified recurrent neural network aka IRNN A recurrent neural sequence architecture using rectified linear hidden units, zero initial recurrent biases, and a trainable recurrent matri…	Curated	Architectures	`AIMech:IdentityInitializedRecurrentNeuralNetwork`	6 claims 1 source
IECO constrained elliptical-mixture classification A constrained classification procedure that models each known class by a mixture of elliptical category distributions, marginalizes category…	Curated	Algorithms	`AIMech:IECOConstrainedMixtureClassification`	5 claims 3 sources
IHSAT A GenSAT variant that chooses the least recently flipped variable among all flips that do not decrease the satisfied-clause count, or among…	Curated	Algorithms	`AIMech:IHSAT`	1 claim 1 source
Image Augmentation Layer A layer that performs image data preprocessing augmentations.	AIO	Layer	`AIO:ImageAugmentationLayer`	Imported
Image Preprocessing Layer A layer that performs image data preprocessing operations.	AIO	Layer	`AIO:ImagePreprocessingLayer`	Imported
Implicit Bias aka Confirmatory Bias An individual bias characterized by unconscious beliefs attitudes feelings associations or stereotypes that affect information processing de…	AIO	Bias	`AIO:ImplicitBias`	Imported
Implicit Language Model aka Implicit LM, Energy-based models… A language model that uses an energy function to score entire sequences instead of factorizing probabilities autoregressively better capturi…	AIO	Model	`AIO:ImplicitLanguageModel`	Imported
Improved consistency training aka iCT (consistency training) The consistency-model training procedure of Song and Dhariwal that learns directly from paired shared-noise data perturbations using a stop-…	Curated	Algorithms	`AIMech:ImprovedConsistencyTraining`	1 claim 1 source
Improved limited discrepancy search aka ILDS Korf’s discrepancy-search variant that uses a supplied maximum search depth and remaining discrepancy count to generate each path to that de…	Curated	Algorithms	`AIMech:ImprovedLimitedDiscrepancySearch`	2 claims 2 sources
Incremental Expectation Maximization aka Incremental EM, IEM (incremental expectation maximization) An EM variant for independent observed cases that refreshes selected cached case posteriors at the current parameters and then fits paramete…	Curated	Algorithms	`AIMech:IncrementalExpectationMaximization`	4 claims 2 sources
Incremental Few-shot Learning aka IFSL A deep neural network trained on a base set of classes and then presented with novel classes, each with few labeled examples.	AIO	Network	`AIO:IncremenetalFewshotLearning`	Imported
Independence Metropolis–Hastings sampling aka Independence Metropolis sampler, IMH A Metropolis–Hastings sampler whose proposal distribution is fixed independently of the current state, with proposal-density ratios still in…	Curated	Algorithms	`AIMech:IndependenceMetropolisHastings`	1 claim 1 source
Individual Bias A bias characterized by a persistent point of view or limited list of such points of view, applied by an individual.	AIO	Bias	`AIO:IndividualBias`	Imported
Infomax Independent Component Analysis aka Infomax ICA, Bell-Sejnowski ICA An unsupervised source-separation learning algorithm that adjusts an invertible square linear transform and biases by the ordinary gradient…	Curated	Algorithms	`AIMech:InfomaxICA`	3 claims 1 source
InfoNCE aka InfoNCE loss A contrastive log-softmax objective that identifies a joint positive among sampled candidates and, under independent marginal-negative sampl…	Curated	Mathematical Methods	`AIMech:InfoNCE`	1 claim 2 sources
Information maximizing self-augmented training aka IMSAT, Information maximising self-augmented training A discrete representation-learning procedure that combines self-augmentation consistency with an information objective, using categorical ou…	Curated	Algorithms	`AIMech:InformationMaximizingSelfAugmentedTraining`	1 claim 4 sources
Information-geometric optimization A stochastic black-box optimization framework that adapts a parametrized sampling distribution using objective ranks and Fisher natural grad…	Curated	Algorithms	`AIMech:InformationGeometricOptimization`	6 claims 1 source
Informed backtracking repair A finite-CSP repair-oriented backtracking controller that uses an existing complete assignment to order repairs while recursively extending…	Curated	Algorithms	`AIMech:InformedBacktrackingRepair`	5 claims 1 source
Informed NegaScout An adversarial game-tree search procedure that augments NegaScout’s minimal-window traversal with recursively retained information from an i…	Curated	Algorithms	`AIMech:InformedNegaScout`	6 claims 1 source
Inherited Bias A processing bias arising when machine learning applications generate inputs for other machine learning algorithms passing on any existing b…	AIO	Bias	`AIO:InheritedBias`	Imported
INLA group node conflict diagnostic A group-wise Bayesian model diagnostic for latent Gaussian models that uses two INLA fits per selected group to compare remaining-data and w…	Curated	Algorithms	`AIMech:INLAGroupNodeConflictDiagnostic`	7 claims 8 sources
Input Layer A layer composed of artificial input neurons that brings the initial data into the system for further processing by subsequent layers.	AIO	Layer	`AIO:InputLayer`	Imported
Input-output hidden Markov model aka IOHMM, Input-output HMM A conditional latent sequence-model family whose discrete hidden-state transitions and state-specific observation distributions depend on th…	Curated	Model Families	`AIMech:InputOutputHiddenMarkovModel`	1 claim 1 source
InputLayer Layer A layer to be used as an entry point into a Network (a graph of layers).	AIO	Layer	`AIO:InputLayerLayer`	Imported
InputSpec Layer A layer that specifies the rank, dtype and shape of every input to a layer.	AIO	Layer	`AIO:InputSpecLayer`	Imported
InstanceNorm1D Layer aka InstanceNorm1D A normalization layer that applies Instance Normalization over a 2D (unbatched) or 3D (batched) input.	AIO	Layer	`AIO:InstanceNorm1DLayer`	Imported
InstanceNorm2D A normalization layer that applies Instance Normalization over a 4D input (a mini-batch of 2D inputs with additional channel dimension).	AIO	Layer	`AIO:InstanceNorm2D`	Imported
InstanceNorm3D Layer aka InstanceNorm3D A normalization layer that applies Instance Normalization over a 5D input (a mini-batch of 3D inputs with additional channel dimension).	AIO	Layer	`AIO:InstanceNorm3DLayer`	Imported
Institutional Bias A systemic bias exhibited at the level of entire institutions where practices or norms result in the favoring or disadvantaging of certain s…	AIO	Bias	`AIO:InstitutionalBias`	Imported
Instruction-Tuned LLM aka Instruction-Tuned Large Language Model, constitutional AI… A large language model which is fine-tuned to follow natural language instructions accurately and safely, learning to map from instructions…	AIO	Model	`AIO:InstructionTunedLLM`	Imported
IntegerLookup Layer A categorical features preprocessing layer that maps integer features to contiguous ranges.	AIO	Layer	`AIO:IntegerLookupLayer`	Imported
Integrated gradients aka IG A feature-attribution method that integrates a prediction's input gradients along the straight path from a chosen baseline to the input.	Curated	Mathematical Methods	`AIMech:IntegratedGradients`	1 claim 1 source
Interaction Network aka Interaction Networks, IN (interaction network) A graph-based neural architecture that applies a shared relation model to supplied directed attributed object relations, sums predicted effe…	Curated	Architectures	`AIMech:InteractionNetwork`	6 claims 1 source
Interpolated variational information bound aka I-alpha bound, Nonlinearly interpolated mutual information lower bound A family of multi-sample mutual-information lower bounds that interpolates the critic’s empirical partition estimate with a positive variati…	Curated	Mathematical Methods	`AIMech:InterpolatedVariationalInformationBound`	3 claims 3 sources
Interpolation consistency training aka ICT A semi-supervised training procedure that encourages a student’s prediction at an interpolated pair of unlabeled inputs to match the same in…	Curated	Algorithms	`AIMech:InterpolationConsistencyTraining`	1 claim 1 source
Interpretation Bias An individual bias where users interpret algorithmic outputs according to their internalized biases and views.	AIO	Bias	`AIO:InterpretationBias`	Imported
Invariant information clustering aka IIC A neural clustering procedure that maximizes mutual information between discrete cluster-assignment variables for paired unlabeled samples,…	Curated	Algorithms	`AIMech:InvariantInformationClustering`	1 claim 2 sources
Inverse compositional spatial transformer network A recurrent learned image-alignment architecture that repeatedly applies one shared geometric predictor to the original source sampled at th…	Curated	Architectures	`AIMech:InverseCompositionalSpatialTransformerNetwork`	5 claims 1 source
IPOP-CMA-ES The original increasing-population restart CMA-ES algorithm, which independently restarts its weighted, rank-mu covariance-matrix-adaptation…	Curated	Algorithms	`AIMech:IPOPCMAES`	6 claims 4 sources
Isomap aka Isometric Feature Mapping A nonlinear dimensionality-reduction algorithm that estimates manifold geodesic distances by shortest paths in a local neighborhood graph an…	Curated	Algorithms	`AIMech:Isomap`	2 claims 2 sources
Iterated conditional modes aka ICM A deterministic conditional-mode optimization algorithm that repeatedly updates one variable to a mode of its conditional distribution given…	Curated	Algorithms	`AIMech:IteratedConditionalModes`	2 claims 2 sources
Iterated local search aka ILS A metaheuristic that builds a single search trajectory among solutions returned by an embedded optimizer by perturbing the current accepted…	Curated	Algorithms	`AIMech:IteratedLocalSearch`	1 claim 1 source
Iterated Wiener Filter aka IWF An iterative MAP image-denoising algorithm that majorizes a fixed Product of Student-t log-potential and alternates response-dependent preci…	Curated	Algorithms	`AIMech:IteratedWienerFilter`	3 claims 1 source
Iterative broadening A tree-search strategy that repeats depth-first search with increasing limits on the number of ordered successors considered at each parent,…	Curated	Algorithms	`AIMech:IterativeBroadening`	5 claims 1 source
Iterative conditional estimation aka ICE An incomplete-data parameter-estimation procedure that repeatedly replaces a chosen complete-data estimator by its conditional expectation g…	Curated	Algorithms	`AIMech:IterativeConditionalEstimation`	1 claim 2 sources
Iterative expansion A recursive heuristic tree-search procedure that repeatedly explores a lowest-valued child within a bound set by its caller and competing ch…	Curated	Algorithms	`AIMech:IterativeExpansion`	6 claims 2 sources
Iterative linear best-first search aka ILBFS An iterative organization of best-first tree search that explicitly retains a principal path and its immediate children, eagerly collapses a…	Curated	Algorithms	`AIMech:IterativeLinearBestFirstSearch`	6 claims 1 source
Iterative threshold search A limited-memory heuristic tree-search algorithm that explores branches within an iteratively revised cost threshold, stores bounds for bran…	Curated	Algorithms	`AIMech:IterativeThresholdSearch`	4 claims 1 source
Iterative weakening A policy for selecting a sufficient search bias by trying a fixed family of search-space restrictions in increasing order of known evaluatio…	Curated	Algorithms	`AIMech:IterativeWeakening`	5 claims 1 source
Iterative-deepening A-star search aka IDA, Iterative-deepening-A A heuristic search algorithm that repeats depth-first passes bounded by f=g+h, starting with the start-state heuristic and raising each cuto…	Curated	Algorithms	`AIMech:IterativeDeepeningAStar`	2 claims 2 sources
ITERSSS* A memory-bounded solution-tree search algorithm for minimax evaluation of a finite uniform alternating game tree that controls an SSS*-style…	Curated	Algorithms	`AIMech:ITERSSSStar`	9 claims 1 source
Joint term-citation model A latent-factor document model that shares each document's fixed topic proportions between categorical term and citation-incidence channels,…	Curated	Model Families	`AIMech:JointTermCitationModel`	2 claims 1 source
Joint unsupervised learning of deep representations and image clusters aka JULE, Joint unsupervised learning An image representation and clustering procedure that alternates periods of graph-based agglomerative merging with convolutional-network upd…	Curated	Algorithms	`AIMech:JointUnsupervisedLearning`	1 claim 2 sources
Jumping Knowledge network aka JK-Net, Jumping Knowledge networks A graph neural architecture that sends intermediate node representations from multiple neighborhood-aggregation depths to a final layer-aggr…	Curated	Architectures	`AIMech:JumpingKnowledgeNetwork`	1 claim 1 source
k-means Clustering that partitions observations around centroids by minimizing within-cluster squared distances.	Curated	Algorithms	`AIMech:KMeans`	1 claim 1 source
K-nearest Neighbor Algorithm aka K-NN, KNN A machine learning task that groups objects by a plurality vote of its neighbors, assigning each object to the class most common among its k…	AIO	MachineLearningTask	`AIO:KnearestNeighborAlgorithm`	Imported
K-nearest Neighbor Classification Algorithm aka K-NN Classification, KNN Classification A classification and clustering that classifies objects by a plurality vote of its neighbors, assigning each object to the class most common…	AIO	MachineLearningTask	`AIO:KnearestNeighborClassificationAlgorithm`	Imported
K-nearest Neighbor Regression Algorithm aka K-NN Regression, KNN Regression A regression analysis that assigns the average of the values of k nearest neighbors to objects.	AIO	MachineLearningTask	`AIO:KnearestNeighborRegressionAlgorithm`	Imported
K-SVD A dictionary-learning algorithm that alternates sparse coding of training samples with sequential updates of each dictionary atom and its ac…	Curated	Algorithms	`AIMech:KSVD`	6 claims 1 source
KADABRA adaptive betweenness approximation aka KADABRA, KADABRA all-node adaptive betweenness approximation An adaptive sampling algorithm for static-graph betweenness that averages internal-node indicators of uniformly sampled shortest paths and s…	Curated	Algorithms	`AIMech:KADABRAAdaptiveBetweenness`	6 claims 2 sources
KADABRA balanced bidirectional shortest-path sampling aka KADABRA balanced bidirectional BFS sampler, KADABRA shortest-path sampler A shortest-path sampling algorithm that expands complete breadth-first-search frontiers from opposite endpoints according to frontier edge v…	Curated	Algorithms	`AIMech:KADABRABalancedBidirectionalPathSampling`	6 claims 2 sources
Karmarkar–Karp differencing aka Karmarkar–Karp heuristic A two-way number-partitioning heuristic that repeatedly replaces the two largest remaining nonnegative residuals by their difference, then r…	Curated	Algorithms	`AIMech:KarmarkarKarpDifferencing`	6 claims 2 sources
Kernel K-Means aka Kernelized K-Means A clustering algorithm that alternates nearest-feature-mean assignments and mean updates to minimize within-cluster squared distances in a k…	Curated	Algorithms	`AIMech:KernelKMeans`	4 claims 2 sources
Kernel Layer A layer that obtains the dot product of input values or subsets of input values.	AIO	Layer	`AIO:KernelLayer`	Imported
Kernel Principal Component Analysis aka Kernel PCA, KPCA A spectral feature-extraction algorithm that performs principal component analysis on centered implicit feature vectors by eigendecomposing…	Curated	Algorithms	`AIMech:KernelPCA`	4 claims 1 source
Kernel SHAP A model-agnostic Shapley-attribution estimator using weighted linear regression on feature-presence subsets.	Curated	Algorithms	`AIMech:KernelSHAP`	1 claim 1 source
Key-Value Memory Network aka KV-MemNN, Key-Value Memory Networks A neural memory architecture that answers a query by attending to keys and reading corresponding values from supplied key-value memory pairs…	Curated	Architectures	`AIMech:KeyValueMemoryNetwork`	6 claims 1 source
Kleinberg nonprincipal hub-authority extraction aka Nonprincipal eigenvector hub-authority extraction A link-analysis procedure that uses paired nonprincipal eigenvectors of the authority and hub Gram matrices of a query-focused directed page…	Curated	Algorithms	`AIMech:KleinbergNonprincipalHubAuthorityExtraction`	5 claims 1 source
Knowledge Transfer aka Inductive Transfer, Adaptation… A training strategy in which knowledge is passed from one entity such as a person organization or system to another facilitating learning an…	AIO	TrainingStrategy	`AIO:KnowledgeTransfer`	Imported
Knowledge-Grounded LLM aka Knowledge-Grounded Large Language Model, factual grounding… A large language model which incorporates external knowledge sources or knowledge bases into the model architecture, enabling it to generate…	AIO	Model	`AIO:KnowledgeGroundedLLM`	Imported
Knuth backtrack-tree estimation aka Knuth tree-size estimator A randomized estimator of additive properties of a fixed backtracking tree that follows a sampled root-to-terminal path and weights each vis…	Curated	Algorithms	`AIMech:KnuthBacktrackTreeEstimation`	5 claims 2 sources
Kohonen Network aka KN, SOFM… A network that is an unsupervised technique producing a low-dimensional representation of high-dimensional data preserving topological struc…	AIO	Network	`AIO:KohonenNetwork`	Imported
L2-loss support vector data description aka L2-loss SVDD, Squared-hinge-loss support vector data description A support-vector data-description algorithm that learns a feature-space sphere using squared-hinge penalties on squared-distance violations,…	Curated	Algorithms	`AIMech:L2LossSupportVectorDataDescription`	4 claims 1 source
Lambda Layer A layer that wraps arbitrary expressions as a Layer object.	AIO	Layer	`AIO:LambdaLayer`	Imported
Language Interface LLM aka Interactive learning A large language model that supports interactive semantic parsing enabling users to provide feedback and corrections to dynamically refine a…	AIO	Model	`AIO:LanguageInterfaceLLM`	Imported
Language Model A model designed to predict the next word in a sequence or assign probabilities to sequences of words in natural language.	AIO	Model	`AIO:LanguageModel`	Imported
Laplacian Eigenmaps aka Laplacian Eigenmap A spectral embedding algorithm that builds a weighted neighborhood graph and uses nonconstant generalized eigenvectors of its graph Laplacia…	Curated	Algorithms	`AIMech:LaplacianEigenmaps`	3 claims 3 sources
Large Language Model aka LLM A language model consisting of a neural network with many parameters (typically billions of weights or more) trained on large quantities of…	AIO	Model	`AIO:LargeLanguageModel`	Imported
Large margin nearest neighbor aka LMNN, Large-margin nearest-neighbor classification… A supervised metric-learning method that fits a positive-semidefinite distance matrix by pulling fixed same-class target neighbors together…	Curated	Algorithms	`AIMech:LargeMarginNearestNeighbor`	2 claims 1 source
LargeVis A dimensionality-reduction and graph-visualization algorithm that constructs an approximate weighted nearest-neighbor graph and learns low-d…	Curated	Algorithms	`AIMech:LargeVis`	1 claim 1 source
Lasso Regression A regression analysis that performs both variable selection and regularization to enhance prediction accuracy and interpretability.	AIO	MachineLearningTask	`AIO:LassoRegression`	Imported
Late Dropout A neural-network training procedure that begins without dropout, activates it after a selected training cutoff and continues optimization wi…	Curated	Algorithms	`AIMech:LateDropout`	5 claims 2 sources
Latent Dirichlet allocation A hierarchical model for collections of discrete observations in which each document draws a Dirichlet-distributed mixture over a fixed fini…	Curated	Model Families	`AIMech:LatentDirichletAllocation`	1 claim 1 source
Layer A structure or network topology in a deep learning model that takes information from previous layers and passes it to the next layer.	AIO	Layer	`AIO:Layer`	Imported
Layer Layer A layer from which other layers can inherit.	AIO	Layer	`AIO:LayerLayer`	Imported
Layer-wise adaptive moments aka LAMB A gradient optimizer that combines coordinate-wise Adam moment scaling with layer-wise normalization of the resulting update direction, opti…	Curated	Algorithms	`AIMech:LayerWiseAdaptiveMoments`	7 claims 2 sources
Layer-wise adaptive rate control aka LARC A parameter-block learning-rate control rule whose clipping form limits a vanilla stochastic-gradient step by using the smaller of a global…	Curated	Algorithms	`AIMech:LayerWiseAdaptiveRateControl`	7 claims 2 sources
Layer-wise adaptive rate scaling A gradient optimization method that multiplies each selected layer or parameter block direction by a scalar based on its current weight L2 n…	Curated	Algorithms	`AIMech:LayerWiseAdaptiveRateScaling`	6 claims 1 source
Layer-wise relevance propagation aka LRP A prediction-decomposition framework that redistributes relevance backward through a classifier's computational layers toward its input feat…	Curated	Mathematical Methods	`AIMech:LayerWiseRelevancePropagation`	1 claim 1 source
LayerNorm Layer aka LayerNorm A normalization layer that applies Layer Normalization over a mini-batch of inputs.	AIO	Layer	`AIO:LayerNormLayer`	Imported
LayerNormalization Layer A normalization layer that applies Layer Normalization over the inputs.	AIO	Layer	`AIO:LayerNormalizationLayer`	Imported
LazyBatchNorm1D Layer aka LazyBatchNorm1D A batch normalization layer that lazily initializes the num_features argument from the input size for 1D data.	AIO	Layer	`AIO:LazyBatchNorm1DLayer`	Imported
LazyBatchNorm2D Layer aka LazyBatchNorm2D A batch normalization layer that lazily initializes the num_features argument from the input size for 2D data.	AIO	Layer	`AIO:LazyBatchNorm2DLayer`	Imported
LazyBatchNorm3D Layer aka LazyBatchNorm3D A batch normalization layer that lazily initializes the num_features argument from the input size for 3D data.	AIO	Layer	`AIO:LazyBatchNorm3DLayer`	Imported
LazyInstanceNorm1D Layer aka LazyInstanceNorm1D A normalization layer that lazily initializes the num_features argument from the input size for 1D data.	AIO	Layer	`AIO:LazyInstanceNorm1DLayer`	Imported
LazyInstanceNorm2D Layer aka LazyInstanceNorm2D A normalization layer that lazily initializes the num_features argument from the input size for 2D data.	AIO	Layer	`AIO:LazyInstanceNorm2DLayer`	Imported
LazyInstanceNorm3D Layer aka LazyInstanceNorm3D A normalization that lazily initializes the num_features argument from the input size for 3D data.	AIO	Layer	`AIO:LazyInstanceNorm3DLayer`	Imported
LeakyReLU Layer An activation layer that applies the leaky rectified linear unit function element-wise.	AIO	Layer	`AIO:LeakyReLULayer`	Imported
Learned-Norm Pooling Unit aka Lp unit, Learned-norm pooling A parameterized neural unit that pools a group of learned linear projections by the power mean of their absolute deviations from learned cen…	Curated	Mathematical Methods	`AIMech:LearnedNormPoolingUnit`	4 claims 1 source
Learning Fair Representations aka LFR, Learned Fair Representations A prototype-based representation-learning algorithm that jointly balances reconstruction, supervised prediction and differences between grou…	Curated	Algorithms	`AIMech:LearningFairRepresentations`	2 claims 2 sources
Learning Hidden Unit Contributions aka LHUC A neural acoustic-model adaptation method that learns speaker- or environment-specific multipliers on hidden-unit activations while keeping…	Curated	Algorithms	`AIMech:LearningHiddenUnitContributions`	5 claims 1 source
Learning real-time A* aka LRTA*, Learning real-time A-star A real-time heuristic learning algorithm that moves to a minimum estimated path-cost neighbor, stores that minimum edge-cost-plus-heuristic…	Curated	Algorithms	`AIMech:LearningRealTimeAStar`	1 claim 2 sources
Least-angle regression aka LARS Regression that advances along directions equiangular to predictors most correlated with the residual.	Curated	Algorithms	`AIMech:LeastAngleRegression`	1 claim 1 source
Least-squares Analysis A regression analysis which approximates the solution of overdetermined systems by minimizing the sum of the squares of the residuals.	AIO	MachineLearningTask	`AIO:LeastsquaresAnalysis`	Imported
Leave-one-out mutual information upper bound aka Leave-one-out variational information upper bound An expectation-level upper bound on mutual information that compares a known conditional density for each paired sample with a mixture of co…	Curated	Mathematical Methods	`AIMech:LeaveOneOutMutualInformationUpperBound`	1 claim 1 source
Lee-Seung Multiplicative Updates aka Lee-Seung NMF Updates The Lee-Seung block multiplicative algorithms for nonnegative matrix factorization, using objective-specific elementwise factor rescaling to…	Curated	Algorithms	`AIMech:LeeSeungMultiplicativeUpdates`	3 claims 1 source
Lifelong Learning LLM aka Continual Learning LLM, Forever Learning… A large language model that continually acquires new knowledge over time without forgetting previously learned information maintaining a bal…	AIO	Model	`AIO:LifelongLearningLLM`	Imported
Lifted structured embedding loss aka Lifted structured loss A metric-learning objective that penalizes a positive pair’s Euclidean distance against negative distances incident to either endpoint, usin…	Curated	Mathematical Methods	`AIMech:LiftedStructuredEmbeddingLoss`	1 claim 2 sources
Limited discrepancy search aka LDS A backtracking tree-search strategy that repeatedly explores paths under an increasing upper limit on deviations from a successor-ordering h…	Curated	Algorithms	`AIMech:LimitedDiscrepancySearch`	3 claims 3 sources
Limited-memory BFGS aka L-BFGS, Limited-memory Broyden-Fletcher-Goldfarb-Shanno A limited-memory quasi-Newton optimization method using a bounded history of parameter and gradient differences to compute approximate inver…	Curated	Algorithms	`AIMech:LBFGS`	1 claim 1 source
Linear discriminant analysis aka LDA Gaussian discriminant classification sharing one covariance matrix across classes.	Curated	Model Families	`AIMech:LinearDiscriminantAnalysis`	1 claim 1 source
Linear Function A mathematical function that has the form f(x) = a + bx.	AIO	MathematicalFunction	`AIO:LinearFunction`	Imported
Linear Regression A regression analysis that is a linear approach for modeling the relationship between a scalar response and one or more explanatory variable…	AIO	MachineLearningTask	`AIO:LinearRegression`	Imported
Linear state-space layer aka LSSL A sequence-to-sequence layer defined by discretizing a linear continuous-time state-space system, with a state recurrence and, for zero init…	Curated	Layers & Modules	`AIMech:LinearStateSpaceLayer`	1 claim 1 source
Linking Bias A use and interpretation bias arising when network attributes obtained from user connections activities or interactions misrepresent true us…	AIO	Bias	`AIO:LinkingBias`	Imported
Lipschitz individual fairness aka Individual fairness (Dwork et al.), Fairness through awareness (Lipschitz criterion) An individual-fairness criterion requiring the distance between the output distributions assigned by a randomized classifier to any two indi…	Curated	Evaluation Criteria	`AIMech:LipschitzIndividualFairness`	1 claim 1 source
Liquid State Machine Network aka LSM A network that is a type of reservoir computer turning time-varying input into spatio-temporal activation patterns.	AIO	Network	`AIO:LiquidStateMachineNetwork`	Imported
List-augmented recurrent neural network aka List RNN A recurrent sequence architecture whose neural controller accesses an external list through a movable read/write head, learning continuous m…	Curated	Architectures	`AIMech:ListAugmentedRecurrentNeuralNetwork`	6 claims 1 source
Liu modified discrete-state Gibbs sampler A discrete conditional sampling algorithm that proposes a category from the full conditional distribution with the current category excluded…	Curated	Algorithms	`AIMech:LiuModifiedGibbsSampler`	5 claims 1 source
Llama clustering aka Lattices by Leveraging Agglomerations and Multiple Ancestors An agglomerative clustering algorithm that unions each current cluster with a nearest neighboring cluster in successive rounds and retains t…	Curated	Algorithms	`AIMech:LlamaClustering`	7 claims 2 sources
Local interpretable model-agnostic explanations aka LIME A prediction-explanation method fitting an interpretable surrogate to locally weighted samples of a model's behavior.	Curated	Algorithms	`AIMech:LIME`	1 claim 1 source
Local outlier factor aka LOF An unsupervised local outlier-scoring procedure that compares each observation's inverse mean reachability distance with those of its tie-in…	Curated	Algorithms	`AIMech:LocalOutlierFactor`	8 claims 3 sources
Local search space learning real-time A* aka LSS-LRTA, Local search space LRTA A real-time heuristic learning algorithm that constructs a bounded local search space with A*, repairs the heuristic values of its expanded…	Curated	Algorithms	`AIMech:LocalSearchSpaceLearningRealTimeAStar`	6 claims 2 sources
Locally Linear Embedding aka LLE A nonlinear dimensionality-reduction algorithm that learns sparse, sum-to-one linear reconstructions of each point from nearby points and co…	Curated	Algorithms	`AIMech:LocallyLinearEmbedding`	2 claims 2 sources
Locally-connected Layer A layer that works similarly to the Convolution1D layer, except that weights are unshared, that is, a different set of filters is applied at…	AIO	Layer	`AIO:LocallyconnectedLayer`	Imported
LocallyConnected1D Layer A locally-connected layer for 1D inputs where each patch of the input is convolved with a different set of filters.	AIO	Layer	`AIO:LocallyConnected1DLayer`	Imported
LocallyConnected2D Layer A locally-connected layer for 2D inputs where each patch of the input is convolved with a different set of filters.	AIO	Layer	`AIO:LocallyConnected2DLayer`	Imported
LocalResponseNorm Layer aka LocalResponseNorm A normalization layer that applies local response normalization over an input signal composed of several input planes.	AIO	Layer	`AIO:LocalResponseNormLayer`	Imported
Log-bilinear language model aka LBL A next-word language architecture that linearly combines position-specific transforms of context-word embeddings and normalizes their biline…	Curated	Architectures	`AIMech:LogBilinearLanguageModel`	1 claim 2 sources
Logarithmic opinion pool aka Log opinion pool, Logarithmic pooling A probability-aggregation method that forms a normalized weighted geometric mean of expert distributions over the same outcomes, using nonne…	Curated	Mathematical Methods	`AIMech:LogarithmicOpinionPool`	1 claim 2 sources
Logistic Regression A regression analysis that estimates the probability of an event occurring by modeling the log-odds of the event as a linear combination of…	AIO	MachineLearningTask	`AIO:LogisticRegression`	Imported
Long Short Term Memory aka LSTM A recurrent neural network with feedback connections that processes entire sequences of data.	AIO	Network	`AIO:LongShortTermMemory`	Imported
Lookup Conditional Distribution Prediction aka Lookup CDP A computational variant of conditional distribution prediction that precomputes or memoizes fixed-model subtree expansion-count estimates fo…	Curated	Algorithms	`AIMech:LookupConditionalDistributionPrediction`	5 claims 1 source
Loss Of Situational Awareness Bias An individual bias occurring when automation leads to humans being unaware of their situation making them unprepared to assume control in co…	AIO	Bias	`AIO:LossOfSituationalAwarenessBias`	Imported
Low-rank adaptation aka LoRA A parameter-efficient adaptation method that freezes pretrained weights and learns additive low-rank matrix updates.	Curated	Algorithms	`AIMech:LoRA`	2 claims 1 source
Low-Resource LLM aka Low-Resource Language Model, low-resource languages… A large language model which is optimized for performance in scenarios with limited data, computational resources, or for languages with spa…	AIO	Model	`AIO:LowResourceLLM`	Imported
Lower Power Genetic Algorithm A processor-configuration optimizer that evolves a symmetry-based network encoding through constrained swap mutation and rank-grouped offspr…	Curated	Algorithms	`AIMech:LowerPowerGeneticAlgorithm`	5 claims 1 source
LPPool1D Layer aka LPPool1D A pooling layer that applies 1D power-average pooling over an input signal composed of several input planes.	AIO	Layer	`AIO:LPPool1DLayer`	Imported
LPPool2D Layer aka LPPool2D A pooling layer that applies 2D power-average pooling over an input signal composed of several input planes.	AIO	Layer	`AIO:LPPool2DLayer`	Imported
LSTM Layer A recurrent layer that implements the Long Short-Term Memory architecture.	AIO	Layer	`AIO:LSTMLayer`	Imported
LSTMCell Layer A layer that processes one step within the whole time sequence input for an LSTM layer.	AIO	Layer	`AIO:LSTMCellLayer`	Imported
MA* A memory-controlled heuristic tree-search algorithm that stores separate lower bounds for absent and all successors, expands promising conti…	Curated	Algorithms	`AIMech:MAStar`	6 claims 1 source
Machine Learning Task aka Machine Learning A process intended to build methods that learn from data.	AIO	MachineLearningTask	`AIO:MachineLearningTask`	Imported
Mamba sequence architecture aka Mamba A neural sequence architecture built from repeated blocks containing input-dependent selective state-space transformations.	Curated	Architectures	`AIMech:Mamba`	1 claim 1 source
Manifold Learning A dimensionality reduction method based on the assumption that observed data lie on a low-dimensional manifold embedded in a higher-dimensio…	AIO	MachineLearningTask	`AIO:ManifoldLearning`	Imported
Manifold Mixup A neural-network training procedure that interpolates paired examples’ representations at a selected network layer and interpolates their la…	Curated	Algorithms	`AIMech:ManifoldMixup`	1 claim 1 source
MAO* A memory-controlled heuristic search algorithm for acyclic AND/OR graphs that expands a marked partial solution graph, revises lower-bound c…	Curated	Algorithms	`AIMech:MAOStar`	6 claims 1 source
Markov Chain aka MC, MP… A network that is a stochastic model describing a sequence of possible events where the probability of each event depends only on the previo…	AIO	Network	`AIO:MarkovChain`	Imported
Markov Chain Monte Carlo Stochastic Approximation Expectation Maximization aka MCMC-SAEM, SAEM-MCMC… A stochastic approximation EM extension that advances a persistent latent-state Markov chain targeting the conditional distribution at the c…	Curated	Algorithms	`AIMech:MarkovChainMonteCarloStochasticApproximationExpectationMaximization`	4 claims 2 sources
Markov decision process aka MDP A sequential decision model with states, actions, Markov transitions, and rewards.	Curated	Model Families	`AIMech:MarkovDecisionProcess`	1 claim 1 source
Markov random field aka MRF, Markov network An undirected graphical probability model associating potential functions with variable groups.	Curated	Model Families	`AIMech:MarkovRandomField`	1 claim 1 source
Masked Language Model aka bidirectional encoder, denoising autoencoder A language model that is trained to predict randomly masked tokens in a sequence based on the remaining unmasked tokens allowing it to build…	AIO	Model	`AIO:MaskedLanguageModel`	Imported
Masking Layer A layer that masks a sequence by using a mask value to skip timesteps.	AIO	Layer	`AIO:MaskingLayer`	Imported
Matched Input-Output Layer An input layer with a shape corresponding to that of the output layer.	AIO	Layer	`AIO:MatchedInputOutputLayer`	Imported
Matching pursuit A greedy fixed-dictionary approximation algorithm that repeatedly selects a unit-norm atom by its absolute correlation with the current resi…	Curated	Algorithms	`AIMech:MatchingPursuit`	5 claims 2 sources
Mathematical Function A mathematical rule that gives the value of a dependent variable corresponding to specified values of one or more independent variables.	AIO	MathematicalFunction	`AIO:MathematicalFunction`	Imported
Max-value Entropy Search A Bayesian global optimization algorithm that chooses evaluations using an approximate information acquisition for the latent maximum functi…	Curated	Algorithms	`AIMech:MaxValueEntropySearch`	6 claims 2 sources
MAXCFU aka Optimization-based counterfactual-fairness sensitivity A multivariate sensitivity algorithm that uses gradient ascent through fitted additive-noise models to search for large counterfactual predi…	Curated	Evaluation Methods	`AIMech:MaxCFU`	2 claims 2 sources
Maximum candidates per node in sequence beam pruning A sequence-beam pruning procedure that limits how many retained candidate extensions may come from the same predecessor hypothesis, discardi…	Curated	Algorithms	`AIMech:PerNodeCandidateBeamPruning`	2 claims 2 sources
Maximum coding likelihood estimation aka Coding likelihood estimation, Coding maximum likelihood estimation A conditional parameter-estimation method that selects mutually non-neighboring sites in a Markov field and maximizes their joint conditiona…	Curated	Algorithms	`AIMech:MaximumCodingLikelihoodEstimation`	1 claim 2 sources
Maximum Layer A merging layer that computes the maximum (element-wise) of a list of inputs.	AIO	Layer	`AIO:MaximumLayer`	Imported
Maximum pseudolikelihood estimation aka MPLE A parameter-estimation method that maximizes the product of a specified model’s sitewise full conditional probabilities or densities evaluat…	Curated	Algorithms	`AIMech:MaximumPseudolikelihoodEstimation`	1 claim 1 source
Maxout Unit aka Maxout A parameterized neural unit that outputs the maximum of a finite group of learned affine functions of its input.	Curated	Mathematical Methods	`AIMech:MaxoutUnit`	5 claims 2 sources
MaxPooling1D Layer aka MaxPool1D, MaxPooling1D A pooling layer that performs max pooling operation for temporal data.	AIO	Layer	`AIO:MaxPooling1DLayer`	Imported
MaxPooling2D Layer aka MaxPool2D, MaxPooling2D A pooling layer that performs max pooling operation for spatial data.	AIO	Layer	`AIO:MaxPooling2DLayer`	Imported
MaxPooling3D Layer aka MaxPool3D, MaxPooling3D A pooling layer that performs max pooling operation for 3D data (spatial or spatio-temporal).	AIO	Layer	`AIO:MaxPooling3DLayer`	Imported
MaxUnpool1D Layer aka MaxUnpool1D A pooling layer that computes a partial inverse of MaxPool1D.	AIO	Layer	`AIO:MaxUnpool1DLayer`	Imported
MaxUnpool2D Layer aka MaxUnpool2D A pooling layer that computes a partial inverse of MaxPool2D.	AIO	Layer	`AIO:MaxUnpool2DLayer`	Imported
MaxUnpool3D Layer aka MaxUnpool3D A pooling layer that computes a partial inverse of MaxPool3D.	AIO	Layer	`AIO:MaxUnpool3DLayer`	Imported
MAX–MIN Ant System aka MMAS An ant-colony optimization algorithm that reinforces solution components from a single selected best ant per iteration, constrains pheromone…	Curated	Algorithms	`AIMech:MaxMinAntSystem`	1 claim 1 source
Mean shift Mode-seeking clustering that moves candidate centers toward local density maxima.	Curated	Algorithms	`AIMech:MeanShift`	1 claim 1 source
Mean Teacher A semi-supervised classifier-training procedure that regularizes a student prediction toward the prediction of a same-architecture teacher w…	Curated	Algorithms	`AIMech:MeanTeacher`	1 claim 2 sources
Mean-field Boltzmann learning aka Mean-field theory learning algorithm A deterministic approximation to Boltzmann-machine parameter learning that substitutes mean-field phase statistics for stochastic equilibriu…	Curated	Algorithms	`AIMech:MeanFieldBoltzmannLearning`	1 claim 1 source
Measurement Bias A selection and sampling bias arising when features and labels are proxies for desired quantities potentially leading to differential perfor…	AIO	Bias	`AIO:MeasurementBias`	Imported
Memory Cell Layer A layer of cells, each with an internal state or weights.	AIO	Layer	`AIO:MemoryCellLayer`	Imported
Memory Network aka Memory Networks A family of learning models that combines an addressable memory with input conversion, memory updating, output inference and response compon…	Curated	Model Families	`AIMech:MemoryNetwork`	6 claims 1 source
Memory-Augmented LLM aka Memory-Augmented Large Language Model, external memory A large language model which incorporates external writable and readable memory components, allowing it to store and retrieve information ov…	AIO	Model	`AIO:MemoryAugmentedLLM`	Imported
Memory-reduced best-first beam search for sequence decoding A capacity-limited variant of per-length best-first sequence beam search that, when its chosen total queue capacity is reached, removes the…	Curated	Algorithms	`AIMech:MemoryReducedSequenceBeamSearch`	2 claims 2 sources
Merging Layer A layer used to merge a list of inputs.	AIO	Layer	`AIO:MergingLayer`	Imported
Meta-Learning A machine learning task that automatically learns from metadata about machine learning experiments.	AIO	MachineLearningTask	`AIO:MetaLearning`	Imported
Meta-Learning LLM aka Meta-Learning Large Language Model, few-shot adaptation… A large language model which is trained in a way that allows it to quickly adapt to new tasks or datasets through only a few examples or fin…	AIO	Model	`AIO:MetaLearningLLM`	Imported
Metric Learning aka Distance Metric Learning A deep neural network that learns a representation function mapping objects into an embedded space.	AIO	Network	`AIO:MetricLearning`	Imported
Metropolis-adjusted Langevin algorithm aka MALA A Metropolis–Hastings sampler that proposes a Gaussian step with drift proportional to the target log-density gradient and corrects the asym…	Curated	Algorithms	`AIMech:MetropolisAdjustedLangevinAlgorithm`	2 claims 2 sources
Metropolis-within-Gibbs sampling aka MWG A componentwise Monte Carlo scheme that uses Metropolis–Hastings transitions targeting full conditional distributions for one or more coordi…	Curated	Algorithms	`AIMech:MetropolisWithinGibbs`	1 claim 1 source
Metropolis–Hastings sampling aka MH A Markov chain Monte Carlo algorithm that proposes a new state from a specified transition distribution and accepts it with the smaller of o…	Curated	Algorithms	`AIMech:MetropolisHastings`	2 claims 2 sources
MEX Operator aka MEX (SimNets) A scalar aggregation operator that returns log(mean(exp(xi times input)))/xi for a nonzero real parameter xi, with its continuous zero-param…	Curated	Mathematical Methods	`AIMech:MEXOperator`	4 claims 1 source
Min-conflicts heuristic aka Min-conflicts A constraint-repair value-selection heuristic that uses a complete assignment to choose a value for a conflicted variable with as few confli…	Curated	Algorithms	`AIMech:MinConflicts`	1 claim 1 source
Minimin search with alpha pruning A bounded single-agent lookahead planner that backs up minimum path-cost-plus-heuristic frontier estimates and prunes branches using an incu…	Curated	Algorithms	`AIMech:MiniminAlphaPruning`	5 claims 2 sources
Minimum Layer A merging layer that computes the minimum (element-wise) of a list of inputs.	AIO	Layer	`AIO:MinimumLayer`	Imported
Mixed memory Markov model A family of compact temporal probability models whose component transition distributions are convex mixtures of transition tables indexed by…	Curated	Model Families	`AIMech:MixedMemoryMarkovModel`	1 claim 1 source
Mixed-membership model for scientific publications A generative document model in which one Dirichlet-distributed membership vector mixes aspect-specific word distributions for an abstract an…	Curated	Model Families	`AIMech:MixedMembershipModelForScientificPublications`	2 claims 1 source
MixMatch A semi-supervised classifier-training procedure that averages predictions over augmented unlabeled inputs, sharpens the resulting soft targe…	Curated	Algorithms	`AIMech:MixMatch`	1 claim 1 source
Mixture density network aka MDN A neural conditional-density architecture whose input-dependent outputs parameterize the mixing weights and component distributions of a fin…	Curated	Architectures	`AIMech:MixtureDensityNetwork`	1 claim 1 source
Mixture-of-Experts LLM aka Mixture-of-Experts Large Language Model, MoE Large Language Model… A large language model which dynamically selects and combines outputs from multiple expert submodels, allowing for efficient scaling by cond…	AIO	Model	`AIO:MixtureofExpertsLLM`	Imported
Mixtures of Probabilistic Principal Component Analyzers aka Mixtures of Probabilistic PCA, MPPCA… A finite Gaussian mixture whose components each have a linear standard-normal latent factor and component-specific isotropic observation noi…	Curated	Model Families	`AIMech:MixturesOfProbabilisticPCA`	5 claims 1 source
MixUp A training-data interpolation procedure that fits a predictor to convex combinations of example inputs and their corresponding targets using…	Curated	Algorithms	`AIMech:MixUp`	1 claim 1 source
Mode Confusion Bias An individual bias occurring when modal interfaces confuse human operators causing actions appropriate for a different mode but incorrect fo…	AIO	Bias	`AIO:ModeConfusionBias`	Imported
Model An abstract representation of a complex system generally assembled as a set of logical mathematical or conceptual properties to simulate or…	AIO	Model	`AIO:Model`	Imported
Model Selection Bias A processing bias introduced when using data to select a single "best" model from many or when an explanatory variable has a weak relationsh…	AIO	Bias	`AIO:ModelSelectionBias`	Imported
Modified Connectionist Q-Learning The original neural action-value learning procedure that uses a selected-next-action temporal-difference error to update weights through acc…	Curated	Algorithms	`AIMech:ModifiedConnectionistQLearning`	6 claims 1 source
Modular Language Model aka Modular LM A language model that consists of multiple specialized components or skills that can be dynamically composed and recombined to solve complex…	AIO	Model	`AIO:ModularLanguageModel`	Imported
Modular LLM aka Modular Large Language Model, component skills… A modular language model that consists of multiple specialized components or skills that can be dynamically composed and recombined to solve…	AIO	Model	`AIO:ModularLLM`	Imported
Momentum contrast aka MoCo A contrastive representation-learning mechanism that maintains a queue of encoded negative keys and produces new keys with an encoder update…	Curated	Algorithms	`AIMech:MomentumContrast`	1 claim 1 source
Monotonic Gaussian process with virtual derivatives aka GP with monotonicity information, Gaussian process with monotonicity information A Gaussian-process inference procedure that promotes monotonicity in selected input coordinates by combining observed outputs with finite vi…	Curated	Algorithms	`AIMech:MonotonicGaussianProcessWithVirtualDerivatives`	4 claims 1 source
Monte Carlo Expectation Maximization aka MCEM, Monte Carlo EM An expectation-maximization method that approximates the current conditional expected complete-data log objective by Monte Carlo integration…	Curated	Algorithms	`AIMech:MonteCarloExpectationMaximization`	3 claims 1 source
MREC A recursive heuristic search algorithm that retains an explicit search graph within available additional memory, explores unstored successor…	Curated	Algorithms	`AIMech:MREC`	4 claims 1 source
Multi-class N-pair loss aka N-pair-mc loss A supervised metric-learning objective that averages a joint positive-versus-multiple-negative log-softmax loss across a batch of positive p…	Curated	Mathematical Methods	`AIMech:MultiClassNPairLoss`	1 claim 1 source
Multi-label text mixture model A generative multi-label document model that selects a label subset and a mixture supported on that subset, then generates each word through…	Curated	Model Families	`AIMech:MultiLabelTextMixtureModel`	2 claims 1 source
Multi-task Bayesian optimization The original Swersky–Snoek–Adams 2013 family of Bayesian optimization procedures that uses a Gaussian process with separable finite-task and…	Curated	Algorithms	`AIMech:MultiTaskBayesianOptimization`	6 claims 1 source
Multi-Task LLM aka Multi-Task Large Language Model, transfer learning A large language model which is trained jointly on multiple language tasks simultaneously, learning shared representations that transfer acr…	AIO	Model	`AIO:MultiTaskLLM`	Imported
Multiclass Classification aka Multinomial Classification A classification focused on methods that classify instances into one of three or more classes.	AIO	MachineLearningTask	`AIO:MulticlassClassification`	Imported
Multiclass Multiple Kernel Maximum Margin Clustering aka Multi-Class Multiple Kernel Clustering A multiclass unsupervised clustering procedure that jointly fits shared nonnegative multiple-kernel weights and latent class-score functions…	Curated	Algorithms	`AIMech:MulticlassMultipleKernelMaximumMarginClustering`	4 claims 1 source
Multidimensional Scaling aka MDS A dimensionality reduction method that translates information about the pairwise distances among a set of objects or individuals into a conf…	AIO	MachineLearningTask	`AIO:MultidimensionalScaling`	Imported
MultiHeadAttention Layer An attention layer that allows the model to attend to information from different representation subspaces.	AIO	Layer	`AIO:MultiHeadAttentionLayer`	Imported
Multilingual LLM aka Multilingual Large Language Model, cross-lingual transfer A large language model that is trained on text from multiple languages learning shared representations that enable zero-shot or few-shot tra…	AIO	Model	`AIO:MultilingualLLM`	Imported
Multimodal Deep Learning A deep neural network that processes and links information using various modalities.	AIO	Network	`AIO:MultimodalDeepLearning`	Imported
Multimodal Fusion LLM aka cross-modal grounding A large language model that learns joint representations across different modalities like text vision and audio in an end-to-end fashion for…	AIO	Model	`AIO:MultimodalFusionLLM`	Imported
Multimodal Language Model aka Mulimodal LM A language model that learns joint representations across different modalities like text vision and audio in an end-to-end fashion for bette…	AIO	Model	`AIO:MultimodalLanguageModel`	Imported
Multimodal Learning A machine learning task that uses multiple modalities of data such as text audio and images to improve learning outcomes.	AIO	MachineLearningTask	`AIO:MultimodalLearning`	Imported
Multimodal LLM aka Multimodal Large Language Model, cross-modal grounding A multimodal large language model that learns joint representations across different modalities like text vision and audio in an end-to-end…	AIO	Model	`AIO:MultimodalLLM`	Imported
Multimodal Prompt-based Language Model A multimodal large language model which processes prompts that include multiple modalities, such as both text and images, to generate releva…	AIO	Model	`AIO:MultimodalPromptbasedLanguageModel`	Imported
Multimodal Transformer aka unified encoder, vision-language model A transformer network that processes and relates information from different modalities such as text images and audio using a shared embeddin…	AIO	Network	`AIO:MultimodalTransformer`	Imported
Multiple-testing node conflict diagnostic A Bayesian evidence-synthesis diagnostic that partitions information at replicated separator nodes, stacks declared contrasts between transf…	Curated	Algorithms	`AIMech:MultipleTestingNodeConflictDiagnostic`	7 claims 3 sources
Multiple-try Metropolis aka MTM A Metropolis sampling algorithm that selects a candidate from several weighted forward proposals, draws a backward reference set containing…	Curated	Algorithms	`AIMech:MultipleTryMetropolis`	1 claim 1 source
Multiple-try Metropolis within Gibbs aka MTM-Gibbs, Griddy Gibbs multiple-try Metropolis A coordinate-update sampler that applies a multiple-try Metropolis transition to a conditional target while holding all other coordinates fi…	Curated	Algorithms	`AIMech:MultipleTryMetropolisWithinGibbs`	1 claim 1 source
Multiply Layer A merging layer that multiplies (element-wise) a list of inputs.	AIO	Layer	`AIO:MultiplyLayer`	Imported
Multiview Kernel K-Means aka MVKKM A multiview clustering algorithm that alternates kernel k-means on a power-weighted combination of fixed view kernels with simplex view-weig…	Curated	Algorithms	`AIMech:MultiviewKernelKMeans`	6 claims 1 source
Multiway Karmarkar–Karp differencing A multiway number-partitioning heuristic that represents partial partitions by normalized bin-load vectors and repeatedly combines two selec…	Curated	Algorithms	`AIMech:MultiwayKarmarkarKarpDifferencing`	6 claims 2 sources
Muon optimizer aka Muon A neural-network optimization method that approximately orthogonalizes momentum-based matrix updates using Newton–Schulz iterations.	Curated	Algorithms	`AIMech:Muon`	1 claim 1 source
Mutual information neural estimation aka MINE, Mutual information neural estimator A mutual-information estimation procedure that trains a neural statistics function to maximize a Donsker–Varadhan objective contrasting join…	Curated	Algorithms	`AIMech:MutualInformationNeuralEstimation`	1 claim 3 sources
NAdam aka Nesterov-accelerated adaptive moment estimation An Adam-family optimizer combining adaptive moment scaling with a Nesterov-style momentum update.	Curated	Algorithms	`AIMech:NAdam`	1 claim 1 source
Naive Bayes aka Naive Bayesian classifier Probabilistic classification assuming feature independence conditional on the class.	Curated	Model Families	`AIMech:NaiveBayes`	1 claim 1 source
NASNet Scheduled DropPath A NASNet training regularizer that stochastically suppresses operation-bearing edges within convolutional cells using a drop probability tha…	Curated	Algorithms	`AIMech:NASNetScheduledDropPath`	6 claims 1 source
Natural Evolution Strategies aka NES A family of black-box optimization algorithms that adapts a parameterized search distribution using estimates of the natural gradient of exp…	Curated	Algorithms	`AIMech:NaturalEvolutionStrategies`	1 claim 1 source
Natural gradient A metric-dependent differential method that maps the coordinate derivatives of a differentiable objective to a tangent vector by the inverse…	Curated	Mathematical Methods	`AIMech:NaturalGradient`	6 claims 3 sources
Natural Language Processing aka NLP A machine learning task focused on the interactions between computers and human language including programming computers to process and anal…	AIO	MachineLearningTask	`AIO:NaturalLanguageProcessing`	Imported
Neal backtracking-suppressed MCMC A finite-state MCMC construction that augments a reversible chain with its preceding state and replaces a conditional resampling step with a…	Curated	Algorithms	`AIMech:NealBacktrackingSuppressedMCMC`	6 claims 2 sources
Nearest-neighbor distance-norm data description aka Nearest neighbor domain description (Angiulli), NNDD distance-norm rule A one-class decision rule that forms the ordered distances from a query to its first k reference neighbors and accepts the query when the L_…	Curated	Algorithms	`AIMech:NearestNeighborDistanceNormDataDescription`	4 claims 2 sources
Nearest-neighbor ratio data description aka Nearest neighbor distance ratio data description, Nearest-neighbor data description (Tax-Duin) A target-class data-description algorithm that scores a query by its distance to a nearest reference observation divided by that observation…	Curated	Algorithms	`AIMech:NearestNeighborRatioDataDescription`	4 claims 2 sources
Nearest-neighbor-chain clustering aka Nearest neighbor chain algorithm, NN-chain clustering An agglomerative clustering algorithm that follows a chain of nearest clusters until its last pair are reciprocal nearest neighbors, merges…	Curated	Algorithms	`AIMech:NearestNeighborChainClustering`	6 claims 7 sources
Neighbourhood components analysis aka Neighborhood components analysis, NCA A supervised metric-learning algorithm that learns a linear transformation by maximizing the expected number of correctly classified trainin…	Curated	Algorithms	`AIMech:NeighborhoodComponentsAnalysis`	1 claim 1 source
Nested antithetic modification A finite conditional transition construction that starts with independent draws from the conditional distribution and successively applies m…	Curated	Algorithms	`AIMech:NestedAntitheticModification`	6 claims 1 source
Network A system of interconnected nodes or entities for communication, computation or data exchange.	AIO	Network	`AIO:Network`	Imported
Neural autoregressive distribution estimator aka NADE A fully visible autoregressive density model whose ordered variable conditionals are computed by neural networks that share input-to-hidden…	Curated	Architectures	`AIMech:NeuralAutoregressiveDistributionEstimator`	1 claim 1 source
Neural GPU aka Neural GPUs A recurrent neural architecture that embeds a complete symbolic sequence in a spatial state grid and repeatedly applies shared convolutional…	Curated	Architectures	`AIMech:NeuralGPU`	6 claims 2 sources
Neural network pushdown automaton aka NNPDA A recurrent state-controller architecture whose signed action output pushes or removes fractional quantities of input symbols on an external…	Curated	Architectures	`AIMech:NeuralNetworkPushdownAutomaton`	6 claims 1 source
Neural probabilistic language model aka NPLM A neural finite-context language architecture that jointly learns a shared word-embedding lookup and a nonlinear predictor of the next-word…	Curated	Architectures	`AIMech:NeuralProbabilisticLanguageModel`	1 claim 1 source
Neural Turing Machine Network aka NTM A deep feedforward network that combines neural network pattern matching with the algorithmic power of programmable computers.	AIO	Network	`AIO:NeuralTuringMachineNetwork`	Imported
Neural variational inference and learning aka NVIL A method for jointly training a directed latent-variable model and an amortized stochastic inference network by maximizing a variational log…	Curated	Algorithms	`AIMech:NeuralVariationalInferenceAndLearning`	3 claims 2 sources
Neuro-Symbolic LLM aka Neuro-Symbolic Large Language Model, knowledge reasoning… A large language model which combines neural language modeling with symbolic reasoning components, leveraging structured knowledge represent…	AIO	Model	`AIO:NeuroSymbolicLLM`	Imported
Newman greedy modularity algorithm aka Newman fast community detection, Newman agglomerative modularity Newman’s direct edge-fraction-matrix algorithm for greedy agglomerative community detection, which starts with singleton vertices, joins adj…	Curated	Algorithms	`AIMech:NewmanGreedyModularity`	7 claims 2 sources
Newman random-walk betweenness matrix computation aka Newman matrix algorithm for random-walk betweenness An exact network-analysis algorithm that computes random-walk betweenness from an embedded inverse of a grounded graph Laplacian, explicitly…	Curated	Algorithms	`AIMech:NewmanRandomWalkBetweennessMatrix`	6 claims 2 sources
NeXO ontology alignment aka AlignOntology An iterative ontology-alignment algorithm that combines shared-terminal set overlap with parent and child neighborhood similarities, then gr…	Curated	Algorithms	`AIMech:NeXOOntologyAlignment`	5 claims 1 source
NeXO ontology construction aka NeXO construction algorithm A network-based ontology-construction procedure that starts from a probabilistic hierarchy of gene communities, removes unsupported binary r…	Curated	Algorithms	`AIMech:NeXOOntologyConstruction`	6 claims 2 sources
Nguyen–Wainwright–Jordan variational bound aka NWJ bound, MINE-f objective… A variational lower bound on Kullback–Leibler divergence that subtracts a product-distribution exponential critic moment from a joint-distri…	Curated	Mathematical Methods	`AIMech:NguyenWainwrightJordanBound`	1 claim 2 sources
No-U-Turn sampler (original slice formulation) The original 2014 slice-based NUTS algorithm, which adapts a Hamiltonian trajectory’s length through randomly directed binary-tree doubling…	Curated	Algorithms	`AIMech:OriginalNoUTurnSampler`	2 claims 2 sources
node2vec aka N2V A machine learning task designed to learn continuous feature representations for nodes in a graph by optimizing a neighborhood-preserving ob…	AIO	MachineLearningTask	`AIO:node2vec`	Imported
node2vec-CBOW aka N2V-CBOW, CBOW A node2vec that predicts the current node from a window of surrounding context nodes, with the order of context nodes not influencing predic…	AIO	MachineLearningTask	`AIO:node2vecCBOW`	Imported
node2vec-SkipGram aka N2V-SkipGram, SkipGram A node2vec that uses the current node to predict the surrounding window of context nodes, weighing nearby context nodes more heavily than di…	AIO	MachineLearningTask	`AIO:node2vecSkipGram`	Imported
Noh–Rieger random-walk centrality aka Random walk centrality of Noh and Rieger A node-scoring method for an undirected random walk that divides each node’s stationary visitation probability by its integrated excess retu…	Curated	Mathematical Methods	`AIMech:NohRiegerRandomWalkCentrality`	6 claims 1 source
Noise Dense Layer A layer that is a densely-connected neural network layer with added noise for regularization.	AIO	Layer	`AIO:NoiseDenseLayer`	Imported
Noisy Input Layer An input layer that adds noise to each value.	AIO	Layer	`AIO:NoisyInputLayer`	Imported
Noisy rectifier A stochastic activation that adds zero-mean noise to a preactivation and then applies the positive-part rectifier, producing h=max(0,a+z).	Curated	Mathematical Methods	`AIMech:NoisyRectifier`	1 claim 1 source
Noisy-OR belief network A directed acyclic binary probabilistic network that models a node’s inactivity as the product of a leak-failure factor and failure factors…	Curated	Architectures	`AIMech:NoisyORBeliefNetwork`	1 claim 1 source
Non-conjugate variational message passing aka NCVMP An approximate inference algorithm that restricts variational blocks to exponential families and updates their natural parameters by matchin…	Curated	Algorithms	`AIMech:NonconjugateVariationalMessagePassing`	7 claims 3 sources
Non-local block aka Non-local neural-network block A neural-network component that aggregates input-dependent pairwise contributions from positions across a representation, projects the aggre…	Curated	Layers & Modules	`AIMech:NonLocalBlock`	1 claim 1 source
Non-local means A classical image-denoising algorithm that estimates each pixel by a normalized average of observed pixel values, assigning exponential simi…	Curated	Algorithms	`AIMech:NonLocalMeans`	5 claims 1 source
Nonlinear autoregressive model with exogenous inputs aka NARX model, Nonlinear autoregressive exogenous model A discrete-time nonlinear input-output model family whose current output is a function of finite lagged outputs and exogenous inputs, plus a…	Curated	Model Families	`AIMech:NonlinearAutoregressiveExogenousModel`	6 claims 2 sources
Nonlinear autoregressive moving average model with exogenous inputs aka NARMAX model A discrete-time nonlinear input-output model family whose current output is a function of finite lagged outputs, exogenous inputs and errors…	Curated	Model Families	`AIMech:NonlinearAutoregressiveMovingAverageExogenousModel`	6 claims 2 sources
Nonnegative Matrix Factorization aka NMF A matrix-decomposition method that represents or approximates a nonnegative data matrix as the product of two entrywise nonnegative factor m…	Curated	Mathematical Methods	`AIMech:NonnegativeMatrixFactorization`	3 claims 1 source
Nonparametric Bayes pachinko allocation model aka NPB PAM, nonparametric PAM A Bayesian pachinko topic-model family using coupled hierarchical Dirichlet-process allocations to infer occupied supertopics and shared sub…	Curated	Model Families	`AIMech:NonparametricBayesPachinkoAllocationModel`	3 claims 1 source
Nonreversible Metropolis uniform update A Metropolis transition algorithm that retains a signed uniform acceptance variable, updates it by wrapped translation, and rescales it afte…	Curated	Algorithms	`AIMech:NonreversibleMetropolisUniformUpdate`	6 claims 1 source
Norm-stabilizer aka Norm stabilization regularization, Norm-stabilizer regularization A recurrent-network regularization procedure that adds a penalty on the average squared change in Euclidean norm between successive selected…	Curated	Algorithms	`AIMech:NormStabilizer`	6 claims 1 source
Normalization A data preparation that transforms data into a standard format or scale typically to reduce redundancy and improve consistency often involvi…	AIO	Preprocessing	`AIO:Normalization`	Imported
Normalization Layer A numerical features preprocessing layer that normalizes continuous features.	AIO	Layer	`AIO:NormalizationLayer`	Imported
Normalized temperature-scaled cross entropy loss aka NT-Xent, NT-Xent loss A contrastive cross-entropy objective that uses cosine-normalized, temperature-scaled similarities to identify a paired positive representat…	Curated	Mathematical Methods	`AIMech:NTXentLoss`	2 claims 2 sources
Novelty SAT heuristic aka Novelty A clause-based SAT local-search heuristic that ranks candidate flips by total violation count with oldest-variable tie breaks, normally sele…	Curated	Algorithms	`AIMech:Novelty`	2 claims 2 sources
Novelty+ SAT heuristic aka Novelty+ A Novelty extension that, at each SAT search step, chooses a random variable from a randomly selected unsatisfied clause with a fixed walk p…	Curated	Algorithms	`AIMech:NoveltyPlus`	2 claims 2 sources
NovoGrad A stochastic gradient optimizer that rescales each parameter block gradient by a scalar running second moment of that block gradient norm be…	Curated	Algorithms	`AIMech:NovoGrad`	7 claims 3 sources
Nu support vector classification aka Nu-SVC, ν-SVC… A supervised binary-classification algorithm that jointly fits a regularized kernel hyperplane and a nonnegative margin level, using nu to r…	Curated	Algorithms	`AIMech:NuSupportVectorClassification`	7 claims 1 source
Nu support vector regression aka Nu-SVR, ν-SVR… A supervised regression algorithm that jointly fits a regularized kernel expansion and a nonnegative constant epsilon-insensitive tube half-…	Curated	Algorithms	`AIMech:NuSupportVectorRegression`	7 claims 1 source
Numerical Features Preprocessing Layer A layer that performs numerical data preprocessing operations.	AIO	Layer	`AIO:NumericalFeaturesPreprocessingLayer`	Imported
Oja Learning Rule aka Oja’s Rule A single-output linear-neuron learning rule that combines a Hebbian input-output weight increment with an output-squared weight decay, obtai…	Curated	Algorithms	`AIMech:OjaLearningRule`	4 claims 1 source
One-class support vector machine aka OCSVM, One-class SVM… A support-estimation algorithm that optimizes a kernel feature-space score relative to the origin using a norm penalty, a learned offset and…	Curated	Algorithms	`AIMech:OneClassSupportVectorMachine`	8 claims 1 source
One-shot Learning aka OSL A deep neural network that classifies objects from one or only a few examples.	AIO	Network	`AIO:OneshotLearning`	Imported
One-vs-one N-pair loss aka N-pair-ovo loss A supervised metric-learning objective that sums separate positive-versus-negative softplus comparisons for each anchor in a batch of positi…	Curated	Mathematical Methods	`AIMech:OneVsOneNPairLoss`	1 claim 1 source
Online hybrid temporal regression planning An online planning-and-scheduling procedure that plans successive jobs by goal-regression A* over logical conditions, variable bindings, sha…	Curated	Algorithms	`AIMech:OnlineHybridTemporalRegressionPlanning`	8 claims 2 sources
OPTICS aka Ordering Points To Identify the Clustering Structure Density-based clustering analysis that orders observations using reachability across neighborhood scales.	Curated	Algorithms	`AIMech:OPTICS`	1 claim 1 source
OPTICS outlier factor aka OPTICS-OF, OPTICS with outlier factors An unsupervised local outlier-scoring procedure that uses self-inclusive, tie-inclusive nearest neighborhoods to compute inverse mean neighb…	Curated	Algorithms	`AIMech:OPTICSOutlierFactor`	7 claims 8 sources
Order-agnostic NADE training aka Order-agnostic training of NADE A stochastic training procedure that shares neural conditional parameters across variable orderings and estimates the order-averaged NADE lo…	Curated	Algorithms	`AIMech:OrderAgnosticNADETraining`	1 claim 1 source
Ordinal LLM aka Ordinal Large Language Model, preference modeling… A large language model that is trained to model ordinal relationships and rank outputs rather than model probability distributions over text…	AIO	Model	`AIO:OrdinalLLM`	Imported
Orthogonal least squares forward selection aka Forward regression orthogonal least squares, FROLS A greedy fixed-candidate regression algorithm that repeatedly adds the column giving the largest reduction in squared residual after joint l…	Curated	Algorithms	`AIMech:OrthogonalLeastSquaresForwardSelection`	7 claims 3 sources
Orthogonal matching pursuit aka OMP A greedy fixed-dictionary approximation algorithm that selects an atom correlated with the current residual and recomputes the approximation…	Curated	Algorithms	`AIMech:OrthogonalMatchingPursuit`	6 claims 3 sources
Otsu thresholding aka Otsu’s method, Otsu threshold selection A histogram-based threshold-selection algorithm that partitions ordered gray levels by maximizing class-weighted between-class variance, equ…	Curated	Algorithms	`AIMech:OtsuThresholding`	1 claim 1 source
Output Layer A layer containing the last neurons in the network that produces given outputs for the program.	AIO	Layer	`AIO:OutputLayer`	Imported
Output-space Predictive Entropy Search A Bayesian global optimization algorithm that selects evaluations using an approximation to information about the latent maximum function va…	Curated	Algorithms	`AIMech:OutputSpacePredictiveEntropySearch`	6 claims 2 sources
Overlapping hierarchical clustering (OHC) aka OHC clustering A graph-based agglomerative clustering algorithm that expands clusters across increasing distance thresholds when the change in induced edge…	Curated	Algorithms	`AIMech:OverlappingHierarchicalClustering`	6 claims 1 source
Pachinko allocation model aka PAM A topic-model family that generates each word by traversing a directed acyclic graph from a root through topic nodes to a word leaf, using p…	Curated	Model Families	`AIMech:PachinkoAllocationModel`	2 claims 1 source
Pachinko allocation topics over time model aka PAMTOT A topic-model family combining pachinko allocation paths with topic-specific continuous timestamp densities at multiple path levels, so that…	Curated	Model Families	`AIMech:PachinkoAllocationTopicsOverTimeModel`	3 claims 1 source
PaCMAP aka Pairwise Controlled Manifold Approximation Projection A nonlinear dimensionality-reduction algorithm that embeds neighbor, mid-near and farther point pairs using separate attractive and repulsiv…	Curated	Algorithms	`AIMech:PaCMAP`	1 claim 1 source
PageRank aka PageRank citation ranking A link-analysis ranking algorithm that assigns node scores using a random walk mixing normalized outgoing-link transitions with teleportatio…	Curated	Algorithms	`AIMech:PageRank`	6 claims 3 sources
Paired differencing method aka PDM A two-way number-partitioning heuristic that sorts residuals and differences disjoint adjacent pairs in whole rounds, carries an unpaired re…	Curated	Algorithms	`AIMech:PairedDifferencing`	6 claims 2 sources
Pairwise Markov chain aka PMC A hidden-state sequence-model family in which the joint process of a hidden variable and its corresponding observation is first-order Markov…	Curated	Model Families	`AIMech:PairwiseMarkovChain`	1 claim 1 source
Pairwise Markov tree aka Arbre de Markov couple A latent-variable tree-model family whose paired hidden and observed states factor into a root distribution and parent-to-child conditional…	Curated	Model Families	`AIMech:PairwiseMarkovTree`	1 claim 1 source
Papadimitriou 2-SAT random walk A randomized 2-SAT search procedure that starts from any complete truth assignment and repeatedly selects an unsatisfied clause and flips a…	Curated	Algorithms	`AIMech:Papadimitriou2SATRandomWalk`	1 claim 1 source
Parallel alternating Newton-like algorithm for APM A block-alternating Newton-like method for fitting an admixture of Poisson Markov random fields through a sparsity-penalized nodewise Poisso…	Curated	Algorithms	`AIMech:ParallelAlternatingNewtonAPM`	2 claims 3 sources
Parallel predictive entropy search A batch Bayesian optimization algorithm that jointly selects parallel evaluations of one scalar objective using approximate information gain…	Curated	Algorithms	`AIMech:ParallelPredictiveEntropySearch`	6 claims 2 sources
Parallel predictive entropy search for multi-objective Bayesian optimization with constraints A batch Bayesian optimization algorithm for multiple objectives and unknown constraints that jointly selects parallel evaluation locations u…	Curated	Algorithms	`AIMech:ParallelPredictiveEntropySearchForMultiObjectiveOptimizationWithConstraints`	6 claims 2 sources
Parallel tempering aka Replica exchange Monte Carlo, Metropolis-coupled Markov chain Monte Carlo A population Monte Carlo method that combines within-temperature target-preserving updates with corrected exchanges between replicas targeti…	Curated	Algorithms	`AIMech:ParallelTempering`	1 claim 1 source
Parameter-Expanded Expectation Maximization aka PX-EM, Parameter-Expanded EM An expectation-maximization construction that fits an expanded complete-data model with auxiliary parameters, reduces its result to the orig…	Curated	Algorithms	`AIMech:ParameterExpandedExpectationMaximization`	4 claims 1 source
Parametric UMAP aka Parametric Uniform Manifold Approximation and Projection A parametric dimensionality-reduction algorithm that trains a neural mapping from input points to embedding coordinates using sampled attrac…	Curated	Algorithms	`AIMech:ParametricUMAP`	2 claims 2 sources
ParamILS An iterated-local-search framework for algorithm configuration that searches finite parameter settings through one-parameter neighborhood mo…	Curated	Algorithms	`AIMech:ParamILS`	1 claim 1 source
Partial least squares regression aka PLS regression, PLSR Regression using latent components chosen to capture predictor-response covariance.	Curated	Mathematical Methods	`AIMech:PartialLeastSquaresRegression`	1 claim 1 source
Partially Informed NegaScout A NegaScout variant for adversarial game-tree search that retains prove-best information near the root of each subtree and the principal var…	Curated	Algorithms	`AIMech:PartiallyInformedNegaScout`	4 claims 1 source
Partially noncentered GLMM variational inference A Bayesian generalized linear mixed-model inference procedure that uses cluster-specific partial noncentering to define independent Gaussian…	Curated	Algorithms	`AIMech:PartiallyNoncenteredGLMMVariationalInference`	7 claims 1 source
Partially observable Markov decision process aka POMDP A Markov decision model in which observations provide incomplete information about the current state.	Curated	Model Families	`AIMech:PartiallyObservableMarkovDecisionProcess`	1 claim 1 source
Particle swarm optimization aka PSO A population-based optimization method that moves candidate particles through a search space using retained velocities and stochastic attrac…	Curated	Algorithms	`AIMech:ParticleSwarmOptimization`	3 claims 3 sources
Path integral clustering aka Agglomerative clustering via maximum incremental path integral, PIC (path integral clustering) An agglomerative clustering algorithm that merges clusters with the greatest increase in their size-normalized sums of discounted random-wal…	Curated	Algorithms	`AIMech:PathIntegralClustering`	1 claim 1 source
Patience-controlled FCFS beam decoding aka FCFS beam decoding with controlled patience A generalization of first-come, first-served sequence beam decoding that retains beam width k for continuing hypotheses but uses a positive…	Curated	Algorithms	`AIMech:PatienceControlledBeamDecoding`	2 claims 2 sources
Peng and Williams Q(lambda) The 1996 tabular incremental Q(lambda) algorithm that combines a direct one-step Q-learning update for the current state-action pair with a…	Curated	Algorithms	`AIMech:PengWilliamsQLambda`	6 claims 2 sources
Perceptron aka FFN, Feed-Forward Network… An artificial neural network with a supervised learning algorithm for binary classification using a linear predictor function.	AIO	Network	`AIO:Perceptron`	Imported
PERCH clustering aka Purity Enhancing Rotations for Cluster Hierarchies An online hierarchical clustering algorithm that inserts observations near existing leaves of a binary cluster tree and uses masking and bal…	Curated	Algorithms	`AIMech:PERCHClustering`	7 claims 4 sources
Permute Layer A reshaping layer that permutes the dimensions of the input according to a given pattern.	AIO	Layer	`AIO:PermuteLayer`	Imported
Persistent contrastive divergence aka PCD A learning algorithm that estimates an energy model’s negative-phase statistics with Markov chains whose states persist across parameter upd…	Curated	Algorithms	`AIMech:PersistentContrastiveDivergence`	1 claim 2 sources
Personalized LLM aka Personalized Large Language Model, user adaptation LLM A large language model that adapts its language modeling and generation to the preferences style and persona of individual users or audience…	AIO	Model	`AIO:PersonalizedLLM`	Imported
Perspective Transformer Nets An image-to-volume neural architecture that combines a convolutional image encoder and volumetric decoder with a supplied-camera projection…	Curated	Architectures	`AIMech:PerspectiveTransformerNets`	6 claims 2 sources
PESC-F An adaptive computation variant of Predictive Entropy Search with Constraints that alternates full inference and acquisition updates with pa…	Curated	Algorithms	`AIMech:PESCF`	6 claims 4 sources
PHATE aka Potential of Heat Diffusion for Affinity-based Transition Embedding A dimensionality-reduction algorithm that computes diffusion transition probabilities, measures Euclidean distances between their negative-l…	Curated	Algorithms	`AIMech:PHATE`	1 claim 1 source
Pi-model aka Π-model A semi-supervised classifier-training procedure that combines labeled cross-entropy with squared disagreement between two stochastic predict…	Curated	Algorithms	`AIMech:PiModel`	1 claim 2 sources
PoClustering edge-clique-cover heuristic An approximate PoClustering algorithm that incrementally extends and prunes clique sets to cover the edges of dissimilarity-threshold graphs…	Curated	Algorithms	`AIMech:PoClusteringEdgeCliqueCover`	6 claims 1 source
PointNet A neural architecture for unordered point clouds that applies shared pointwise feature extraction and symmetric max pooling to produce a glo…	Curated	Architectures	`AIMech:PointNet`	1 claim 1 source
PointNet++ A hierarchical point-set neural architecture that repeatedly samples centroids, groups metric neighborhoods and applies local PointNet featu…	Curated	Architectures	`AIMech:PointNetPlusPlus`	1 claim 1 source
Poisson generalized root model aka Poisson GRM A generalized root probability model on unbounded nonnegative integer counts, with factorial base measures and symmetric products of j-th ro…	Curated	Model Families	`AIMech:PoissonGeneralizedRootModel`	1 claim 1 source
Poisson square root graphical model aka Poisson SQR, Poisson square root Markov random field A square-root graphical model on unbounded nonnegative integer counts with factorial base measures, unary square-root and linear count terms…	Curated	Model Families	`AIMech:PoissonSquareRootGraphicalModel`	1 claim 2 sources
Policy Layer A layer that, after taking a set of states or values as input, predicts a probability distribution of actions to take.	AIO	Layer	`AIO:PolicyLayer`	Imported
Pooling Layer A layer that serves to mitigate the sensitivity of convolutional layers to location and spatially downsample representations.	AIO	Layer	`AIO:PoolingLayer`	Imported
Popularity Bias A selection and sampling bias where more popular items are more exposed under-representing less popular items.	AIO	Bias	`AIO:PopularityBias`	Imported
Population Based Augmentation aka PBA An augmentation-schedule learning procedure that jointly trains a population of child classifiers and evolves their augmentation hyperparame…	Curated	Algorithms	`AIMech:PopulationBasedAugmentation`	2 claims 3 sources
Population Based Training aka PBT A population-based neural-network training procedure that interleaves parameter updates with performance-guided copying of partially trained…	Curated	Algorithms	`AIMech:PopulationBasedTraining`	1 claim 1 source
Population Bias A selection and sampling bias characterized by systematic distortions in demographics or other user characteristics between represented user…	AIO	Bias	`AIO:PopulationBias`	Imported
Population-based incremental learning aka PBIL An optimization method that samples candidate solutions from a probability-vector representation and incrementally moves that representation…	Curated	Algorithms	`AIMech:PopulationBasedIncrementalLearning`	1 claim 1 source
Power iteration clustering aka PIC (power iteration clustering) A clustering algorithm that uses an early-stopped power iteration of a normalized similarity matrix to embed observations and then applies k…	Curated	Algorithms	`AIMech:PowerIterationClustering`	2 claims 2 sources
Preconditioned Crank–Nicolson Langevin sampling aka pCNL A Metropolis-corrected Gaussian-reference sampler that preconditions the potential-gradient drift by the reference covariance and uses a sca…	Curated	Algorithms	`AIMech:PreconditionedCrankNicolsonLangevin`	1 claim 1 source
Preconditioned Crank–Nicolson sampling aka pCN A Metropolis sampler for a Gaussian-reference target whose proposal combines the current state with an independent draw from that reference…	Curated	Algorithms	`AIMech:PreconditionedCrankNicolson`	1 claim 1 source
Predictive Entropy Search A Bayesian global optimization algorithm that approximates information about the global maximizer by subtracting maximizer-conditioned predi…	Curated	Algorithms	`AIMech:PredictiveEntropySearch`	6 claims 3 sources
Predictive entropy search for multi-objective Bayesian optimization A Bayesian multi-objective optimization algorithm that selects evaluations using an approximate information gain about the Pareto set, compu…	Curated	Algorithms	`AIMech:PredictiveEntropySearchForMultiObjectiveOptimization`	6 claims 3 sources
Predictive entropy search for multi-objective Bayesian optimization with constraints A Bayesian optimization algorithm for multiple objectives and unknown constraints that selects evaluations using approximate information gai…	Curated	Algorithms	`AIMech:PredictiveEntropySearchForMultiObjectiveOptimizationWithConstraints`	6 claims 4 sources
Predictive Entropy Search with Constraints A Bayesian optimization algorithm for an unknown objective and unknown inequality constraints that selects evaluations using an approximatio…	Curated	Algorithms	`AIMech:PredictiveEntropySearchWithConstraints`	6 claims 3 sources
PReLU Layer An activation layer that applies parametric rectified linear unit function element-wise.	AIO	Layer	`AIO:PReLULayer`	Imported
Preprocessing A process applied to raw data before it is used in a machine learning model, including tasks such as normalization, scaling, encoding, and t…	AIO	Preprocessing	`AIO:Preprocessing`	Imported
Preprocessing Layer A layer that performs data preprocessing operations.	AIO	Layer	`AIO:PreprocessingLayer`	Imported
Presentation Bias An individual bias arising from how information is presented on the Web via a user interface due to rating or ranking of output or through u…	AIO	Bias	`AIO:PresentationBias`	Imported
Principal Component Analysis aka PCA A dimensionality reduction method for analyzing large datasets with high-dimensional features per observation increasing data interpretabili…	AIO	MachineLearningTask	`AIO:PrincipalComponentAnalysis`	Imported
Principal Curves aka Hastie–Stuetzle Principal Curves A nonlinear statistical summary defined by a smooth curve that is self-consistent for a data distribution: almost every point on the curve e…	Curated	Mathematical Methods	`AIMech:PrincipalCurves`	4 claims 1 source
Probabilistic Graphical Model aka Graphical Model, PGM… A machine learning task in which a graph expresses the conditional dependence structure between random variables.	AIO	MachineLearningTask	`AIO:ProbabilisticGraphicalModel`	Imported
Probabilistic Hidden Layer A hidden layer that estimates the probability of a sample being within a certain category.	AIO	Layer	`AIO:ProbabilisticHiddenLayer`	Imported
Probabilistic latent semantic analysis aka PLSA, Probabilistic latent semantic indexing… A latent-class model of document–word or other dyadic co-occurrences that represents their joint probability as a mixture of conditionally i…	Curated	Model Families	`AIMech:ProbabilisticLatentSemanticAnalysis`	1 claim 2 sources
Probabilistic Principal Component Analysis aka PPCA A linear Gaussian latent-variable model with a standard-normal latent prior and isotropic observation noise, whose maximum-likelihood loadin…	Curated	Model Families	`AIMech:ProbabilisticPCA`	4 claims 1 source
Probabilistic Topic Model A probabilistic graphical model that uses statistical techniques to analyze the words in each text to discover common themes their connectio…	AIO	MachineLearningTask	`AIO:ProbabilisticTopicModel`	Imported
Probability of improvement acquisition An acquisition criterion for scalar optimization that scores a candidate by the predictive probability of meeting a specified improvement th…	Curated	Mathematical Methods	`AIMech:ProbabilityOfImprovementAcquisition`	6 claims 2 sources
Processing Bias aka Validation Bias A computational bias resulting from judgment modulated by affect influenced by the level of efficacy and efficiency in information processin…	AIO	Bias	`AIO:ProcessingBias`	Imported
Product of experts aka PoE, Products of experts A probabilistic model family that combines expert factors over the same observations by multiplying their values and normalizing the product…	Curated	Model Families	`AIMech:ProductOfExperts`	1 claim 2 sources
Product of hidden Markov models aka PoHMM, Products of hidden Markov models A sequence-model family that multiplies the marginal probabilities assigned to a complete observation sequence by several hidden Markov mode…	Curated	Model Families	`AIMech:ProductOfHiddenMarkovModels`	1 claim 2 sources
Product of Student-t aka Product of Student-t Model, PoT A normalized energy-based density on continuous observations formed from products of Student-t-shaped factors of linear filter responses, wi…	Curated	Model Families	`AIMech:ProductOfStudentT`	4 claims 1 source
Professor forcing An adversarial recurrent-network training procedure that retains teacher-forced likelihood learning while training an auxiliary discriminato…	Curated	Algorithms	`AIMech:ProfessorForcing`	6 claims 1 source
Prompt-based Fine-Tuning LLM aka Prompt-based Fine-Tuning Large Language Model, Prompt-tuned Large Language Model… A large language model which is fine-tuned on a small number of examples or prompts, rather than full task datasets. This allows for rapid a…	AIO	Model	`AIO:PromptbasedFineTuningLLM`	Imported
Proportional Hazards Model A regression analysis for survival analysis where the unique effect of a unit increase in a covariate is multiplicative with respect to the…	AIO	MachineLearningTask	`AIO:ProportionalHazardsModel`	Imported
Prototype-based domain description aka PDD radius-offset rule A one-class decision rule that accepts a query when its metric distance to at least one prototype, plus that prototype's stored radius offse…	Curated	Algorithms	`AIMech:PrototypeBasedDomainDescription`	4 claims 1 source
Proximal policy optimization aka PPO A family of policy-gradient algorithms alternating collected interaction data with repeated optimization of a surrogate objective using clip…	Curated	Algorithms	`AIMech:ProximalPolicyOptimization`	1 claim 1 source
Pseudo-Label A semi-supervised neural-network training procedure that recomputes hard labels from the model’s most probable class for unlabeled examples…	Curated	Algorithms	`AIMech:PseudoLabel`	2 claims 1 source
Pseudo-linear regression estimation aka Pseudo-linear regression algorithm A family of recursive coefficient estimators that uses the current regressor as a surrogate prediction sensitivity, omitting derivatives thr…	Curated	Algorithms	`AIMech:PseudoLinearRegressionEstimation`	5 claims 1 source
Q-learning A model-free reinforcement-learning method that incrementally updates action-value estimates toward an observed reward plus the discounted m…	Curated	Algorithms	`AIMech:QLearning`	1 claim 1 source
Q-routing A distributed adaptive packet-routing algorithm that learns destination-specific delivery-time estimates by combining observed local queue a…	Curated	Algorithms	`AIMech:QRouting`	1 claim 1 source
Quadratic discriminant analysis aka QDA Gaussian discriminant classification with class-specific covariance matrices.	Curated	Model Families	`AIMech:QuadraticDiscriminantAnalysis`	1 claim 1 source
Quadratic Poisson graphical model aka QPGM, Quadratic Poisson Markov random field A graphical probability model on nonnegative integer counts whose joint log mass contains unary linear terms, site quadratic terms and symme…	Curated	Model Families	`AIMech:QuadraticPoissonGraphicalModel`	1 claim 2 sources
R-Novelty SAT heuristic aka R-Novelty A Novelty-derived SAT heuristic whose choice between the best and second-best flips depends on their objective-score gap when the best varia…	Curated	Algorithms	`AIMech:RNovelty`	2 claims 3 sources
R-Novelty+ SAT heuristic aka R-Novelty+ The 1999 R-Novelty extension that replaces its periodic random override with a fixed per-step probability of a random clause-variable flip a…	Curated	Algorithms	`AIMech:RNoveltyPlus`	3 claims 3 sources
Radial Basis Network aka RBFN, RBN… A deep feedforward network that uses radial basis functions as activation functions for pattern recognition and interpolation.	AIO	Network	`AIO:RadialBasisNetwork`	Imported
Radicchi edge-clustering community detection aka Radicchi divisive algorithm, modified edge-clustering community detection A divisive graph-community algorithm family that repeatedly removes edges with the lowest modified cycle-based edge-clustering score, update…	Curated	Algorithms	`AIMech:RadicchiEdgeClustering`	7 claims 1 source
RandAugment An image-augmentation procedure that applies a uniformly sampled sequence of operations sharing one magnitude parameter, reducing augmentati…	Curated	Algorithms	`AIMech:RandAugment`	1 claim 1 source
Random Effects Model aka REM A regression analysis where the model parameters are random variables.	AIO	MachineLearningTask	`AIO:RandomEffectsModel`	Imported
Random Forest An ensemble learning method for classification regression and other tasks that constructs a multitude of decision trees during training.	AIO	MachineLearningTask	`AIO:RandomForest`	Imported
Random Online Aggressive Racing aka ROAR, Random Online Adaptive Racing An algorithm-configuration procedure that proposes uniformly random parameter settings and compares each challenger with an incumbent throug…	Curated	Algorithms	`AIMech:RandomOnlineAggressiveRacing`	1 claim 1 source
Random Search for Hyperparameter Optimization aka Random Hyperparameter Search A hyperparameter optimization procedure that draws trial configurations independently from a specified search distribution, evaluates their…	Curated	Algorithms	`AIMech:RandomSearchHyperparameterOptimization`	1 claim 1 source
Random-only abstraction for abstraction sampling aka Random-only abstraction sampling, simpleRand abstraction… A randomized abstraction rule for graphical-model sampling that uniformly permutes the current search nodes and divides that order into grou…	Curated	Mathematical Methods	`AIMech:RandomOnlyAbstractionSampling`	6 claims 1 source
Random-walk Metropolis–Hastings sampling aka RWMH A Metropolis–Hastings sampler that proposes a new state by adding an increment drawn from a fixed distribution independent of the current st…	Curated	Algorithms	`AIMech:RandomWalkMetropolisHastings`	1 claim 1 source
RandomBrightness Layer An image preprocessing layer that randomly adjusts brightness during training.	AIO	Layer	`AIO:RandomBrightnessLayer`	Imported
RandomContrast Layer An image preprocessing layer that randomly adjusts contrast during training.	AIO	Layer	`AIO:RandomContrastLayer`	Imported
RandomCrop Layer An image preprocessing layer that randomly crops images during training.	AIO	Layer	`AIO:RandomCropLayer`	Imported
RandomFlip Layer An image preprocessing layer that randomly flips images during training.	AIO	Layer	`AIO:RandomFlipLayer`	Imported
RandomHeight Layer An image preprocessing layer that randomly varies image height during training.	AIO	Layer	`AIO:RandomHeightLayer`	Imported
Randomized latent score conflict diagnostic aka Randomised latent score conflict diagnostic A Bayesian hierarchical-model diagnostic that freezes draws from a parent posterior excluding selected child data, draws child latent parame…	Curated	Algorithms	`AIMech:RandomizedLatentScoreConflictDiagnostic`	8 claims 1 source
RandomRotation Layer An image preprocessing layer that randomly rotates images during training.	AIO	Layer	`AIO:RandomRotationLayer`	Imported
RandomTranslation Layer An image preprocessing layer that randomly translates images during training.	AIO	Layer	`AIO:RandomTranslationLayer`	Imported
RandomWidth Layer An image preprocessing layer that randomly varies image width during training.	AIO	Layer	`AIO:RandomWidthLayer`	Imported
RandomZoom Layer An image preprocessing layer that randomly zooms in or out on images during training.	AIO	Layer	`AIO:RandomZoomLayer`	Imported
Rank-based Ant System aka ASrank An Ant System variant that weights pheromone deposits from a selected number of the current iteration’s best tours by rank and adds a separa…	Curated	Algorithms	`AIMech:RankBasedAntSystem`	1 claim 1 source
Ranking Bias An anchoring bias characterized by the idea that top-ranked results are the most relevant and important leading to more clicks than other re…	AIO	Bias	`AIO:RankingBias`	Imported
RAPID support vector data description sampling aka RAPID, Reducing samples by pruning of inlier densities A density-based training-subset selection method for support vector data description that prefilters low-density observations and greedily r…	Curated	Preprocessing Methods	`AIMech:RapidSupportVectorDataDescriptionSampling`	8 claims 5 sources
Rashomon Effect Bias aka Rashomon Effect, Rashomon Principle An individual bias characterized by differences in perspective memory recall interpretation and reporting of the same event by multiple pers…	AIO	Bias	`AIO:RashomonEffectBias`	Imported
Rate-adapting Poisson model aka RAP A harmonium model family coupling unbounded visible Poisson counts to finite binomial hidden variables through bilinear interactions that sh…	Curated	Model Families	`AIMech:RateAdaptingPoissonModel`	3 claims 1 source
RBFS-epsilon aka RBFSϵ A recursive best-first search variant that adds a finite nonnegative epsilon tolerance to the competitive expansion threshold, retaining the…	Curated	Algorithms	`AIMech:RBFSEpsilon`	4 claims 1 source
RBFS-kth-root aka RBFSkthrt A bounded-suboptimal recursive best-first search variant that divides a quality budget w between a heuristic factor w^((k-1)/k) and a compet…	Curated	Algorithms	`AIMech:RBFSKthRoot`	4 claims 1 source
Real-time A* aka RTA*, Real-time A-star A real-time heuristic search algorithm that moves to a neighbor with minimum edge-cost-plus-heuristic estimate and stores the second-best su…	Curated	Algorithms	`AIMech:RealTimeAStar`	1 claim 2 sources
Real-Time Adaptive A* aka RTAA* A real-time heuristic search algorithm that repeatedly runs bounded forward A*, updates every expanded state to the selected next-to-expand…	Curated	Algorithms	`AIMech:RealTimeAdaptiveAStar`	8 claims 2 sources
Real-time recurrent learning aka RTRL A recurrent-network training algorithm that propagates state sensitivities to adjustable weights forward in time and contracts those sensiti…	Curated	Algorithms	`AIMech:RealTimeRecurrentLearning`	6 claims 1 source
Real-valued neural autoregressive density estimator aka RNADE, Real-valued autoregressive density estimator A fully visible neural autoregressive density architecture for real-valued vectors that shares input-to-hidden parameters across ordered sca…	Curated	Architectures	`AIMech:RealValuedNeuralAutoregressiveDensityEstimator`	1 claim 2 sources
Reasoning LLM aka Rational Large Language Model, Reasoning Large Language Model… A large language model that incorporates explicit reasoning capabilities leveraging logical rules axioms or external knowledge to make deduc…	AIO	Model	`AIO:ReasoningLLM`	Imported
Reciprocal-nearest-neighbors supported clustering aka RS clustering A hierarchical clustering algorithm that follows nearest-neighbor chains to construct sub-clustering trees around reciprocal pairs, prunes o…	Curated	Algorithms	`AIMech:ReciprocalNearestNeighborsSupportedClustering`	5 claims 1 source
Rectified Adam aka RAdam An Adam-family optimizer that rectifies its adaptive update using a time-dependent estimate of the effective history of the second-moment st…	Curated	Algorithms	`AIMech:RAdam`	1 claim 1 source
Rectified flow aka RF (rectified flow) A transport-learning method that regresses a velocity field on endpoint differences along straight interpolations of coupled samples and use…	Curated	Algorithms	`AIMech:RectifiedFlow`	2 claims 2 sources
Recurrent Layer A layer composed of recurrent units with the number equal to the hidden size of the layer.	AIO	Layer	`AIO:RecurrentLayer`	Imported
Recurrent Neural Network aka RN, RecNN… A network with connections forming a directed graph along a temporal sequence enabling dynamic behavior.	AIO	Network	`AIO:RecurrentNeuralNetwork`	Imported
Recurrent temporal restricted Boltzmann machine aka RTRBM A recurrent neural sequence architecture whose deterministic state is a conditional RBM hidden-probability vector and sets the next step’s h…	Curated	Architectures	`AIMech:RecurrentTemporalRestrictedBoltzmannMachine`	1 claim 1 source
Recursive best-first search aka RBFS A recursive search algorithm that explores the best stored subtree alternative within an upper bound and conditionally passes a previously b…	Curated	Algorithms	`AIMech:RecursiveBestFirstSearch`	2 claims 2 sources
Recursive best-first search with controlled re-expansion aka RBFS_CR, RBFS with bounded overhead An RBFS variant that estimates subtree evaluation-value distributions and inflates backed-up values to make later visits expand geometricall…	Curated	Algorithms	`AIMech:RBFSControlledReexpansion`	2 claims 2 sources
Recursive Language Model aka RLM, Compositional generalization A deep neural network that uses recursive neural network architectures like TreeLSTMs to learn syntactic composition functions improving sys…	AIO	Network	`AIO:RecursiveLanguageModel`	Imported
Recursive LLM aka Recursive Large Language Model, Self-Attending Large Language Model… A language model that uses recursive neural network architectures like TreeLSTMs to learn syntactic composition functions improving systemat…	AIO	Model	`AIO:RecursiveLLM`	Imported
Recursive Neural Network aka RecuNN, RvNN A deep neural network that recursively applies weights over structured input to generate structured or scalar predictions.	AIO	Network	`AIO:RecursiveNeuralNetwork`	Imported
Recursive prediction-error estimation aka Recursive prediction error method A recursive parameter-estimation method that incrementally adjusts a parameterized predictor using prediction errors and search directions b…	Curated	Algorithms	`AIMech:RecursivePredictionErrorEstimation`	6 claims 1 source
Regression Analysis aka Regression analysis, Regression model A set of statistical processes for estimating the relationships between a dependent variable and one or more independent variables.	AIO	MachineLearningTask	`AIO:RegressionAnalysis`	Imported
Regularization Layer A layer that applies penalties on layer parameters or layer activity during optimization summed into the loss function that the network opti…	AIO	Layer	`AIO:RegularizationLayer`	Imported
Regularized Evolution aka Aging Evolution An evolutionary neural-architecture search algorithm that selects a parent by recorded validation accuracy from a uniformly sampled tourname…	Curated	Algorithms	`AIMech:RegularizedEvolution`	6 claims 2 sources
Regularized information maximization aka RIM, Regularised information maximisation A discriminative clustering framework that fits conditional class probabilities by maximizing empirical input–assignment mutual information…	Curated	Algorithms	`AIMech:RegularizedInformationMaximization`	1 claim 1 source
REINFORCE aka REINFORCE algorithm A family of stochastic reinforcement-learning update rules that multiply a sampled reward relative to an admissible baseline by the derivati…	Curated	Algorithms	`AIMech:REINFORCE`	3 claims 2 sources
Reinforcement Learning A machine learning task focused on methods that do not require labeled input/output pairs or explicit correction of sub-optimal actions focu…	AIO	MachineLearningTask	`AIO:ReinforcementLearning`	Imported
Reinforcement Learning LLM aka RL-Large Language Model, Reinforcement Learning Large Language Model… A large language model that is fine-tuned using reinforcement learning where the model receives rewards for generating text that satisfies c…	AIO	Model	`AIO:ReinforcementLearningLLM`	Imported
Rejection sampling aka Accept-reject sampling A random-variate generation algorithm that draws proposals from a normalized envelope dominating an unnormalized target and accepts each wit…	Curated	Algorithms	`AIMech:RejectionSampling`	1 claim 1 source
Rejection-driven independence Metropolis sampling An independence Metropolis sampler whose proposals are generated by a rejection procedure with a fixed possibly non-dominating envelope, fol…	Curated	Algorithms	`AIMech:RejectionDrivenIndependenceMetropolis`	2 claims 2 sources
Relation network A reusable neural module for relational reasoning that applies a shared learned function to pairs of object representations, sums the result…	Curated	Layers & Modules	`AIMech:RelationNetwork`	6 claims 1 source
Relevance-weighted topic distillation aka Relevance-conscious topic distillation, Chakrabarti relevance-weighted distillation An iterative web-link ranking procedure that alternates authority and hub score propagation using destination relevance for forward contribu…	Curated	Algorithms	`AIMech:RelevanceWeightedTopicDistillation`	5 claims 1 source
Relevant component analysis aka RCA A partially supervised linear metric-learning procedure that estimates within-group covariance from positive equivalence constraints and whi…	Curated	Algorithms	`AIMech:RelevantComponentAnalysis`	2 claims 1 source
ReLU Function aka ReLU, Rectified Linear Unit A mathematical function that returns max(x 0) the element-wise maximum of 0 and the input tensor.	AIO	MathematicalFunction	`AIO:ReLUFunction`	Imported
ReLU Layer An activation layer that applies the rectified linear unit function element-wise.	AIO	Layer	`AIO:ReLULayer`	Imported
ReMixMatch A semi-supervised classifier-training procedure that adjusts weak-view guessed labels toward an estimated class prior, sharpens and anchors…	Curated	Algorithms	`AIMech:ReMixMatch`	1 claim 4 sources
RepeatVector Layer A reshaping layer that repeats the input n times.	AIO	Layer	`AIO:RepeatVectorLayer`	Imported
Replacing eligibility traces An eligibility-trace update that replaces a visited state’s eligibility by one while geometrically attenuating other state traces, preservin…	Curated	Mathematical Methods	`AIMech:ReplacingEligibilityTraces`	5 claims 1 source
Replicated Softmax An undirected document model with binary hidden units and a length-dependent set of categorical word units that share visible-to-hidden weig…	Curated	Architectures	`AIMech:ReplicatedSoftmax`	1 claim 1 source
Representation Bias A selection and sampling bias due to non-random sampling of subgroups making trends non-generalizable to new populations.	AIO	Bias	`AIO:RepresentationBias`	Imported
Representation Learning aka Feature Learning A deep neural network that discovers representations required for feature detection or classification from raw data.	AIO	Network	`AIO:RepresentationLearning`	Imported
Rescaling Layer An image preprocessing layer that rescales input values to a new range.	AIO	Layer	`AIO:RescalingLayer`	Imported
Reshape Layer A reshaping layer that reshapes the inputs into the given shape.	AIO	Layer	`AIO:ReshapeLayer`	Imported
Reshaping Layer aka Reshape Layer A layer that is used to change the shape of the input.	AIO	Layer	`AIO:ReshapingLayer`	Imported
Residual Attention Network aka RAN (residual attention) A convolutional-network architecture that stacks attention modules combining trunk features with learned bottom-up and top-down masks throug…	Curated	Architectures	`AIMech:ResidualAttentionNetwork`	1 claim 1 source
Residual Neural Network aka DRN, Deep Residual Network… A deep neural network that employs skip connections to bypass layers facilitating learning of residual functions.	AIO	Network	`AIO:ResidualNeuralNetwork`	Imported
Resilient backpropagation aka Rprop A gradient-based optimization method that adapts coordinate step sizes using successive gradient signs and takes sign-directed parameter ste…	Curated	Algorithms	`AIMech:ResilientBackpropagation`	1 claim 1 source
Resizing Layer An image preprocessing layer that resizes images to a target size.	AIO	Layer	`AIO:ResizingLayer`	Imported
Restricted Boltzmann Machine aka RBM A Boltzmann machine network that learns the probability distribution of its input data.	AIO	Network	`AIO:RestrictedBoltzmannMachine`	Imported
Restricted Boltzmann Machine Collaborative Filtering aka RBM collaborative filtering, RBM-CF A family of shared-parameter restricted Boltzmann models for categorical user-item ratings, with a user-specific visible set and optional co…	Curated	Model Families	`AIMech:RestrictedBoltzmannMachineCollaborativeFiltering`	4 claims 1 source
Retentive network aka RetNet An autoregressive neural sequence architecture that stacks pre-normalized residual blocks combining gated multi-scale retention with feedfor…	Curated	Architectures	`AIMech:RetNet`	1 claim 1 source
Retrieval-Augmented LLM aka Retrieval-Augmented Large Language Model, knowledge grounding… A large language model which combines a pre-trained language model with a retrieval system that can access external knowledge sources. This…	AIO	Model	`AIO:RetrievalAugmentedLLM`	Imported
Reweighted wake-sleep aka RWS A learning procedure for paired generative and inference networks that uses multiple inference samples and normalized importance weights for…	Curated	Algorithms	`AIMech:ReweightedWakeSleep`	1 claim 1 source
Ridge Regression A regression analysis that estimates the coefficients of multiple regression models in scenarios where the independent variables are highly…	AIO	MachineLearningTask	`AIO:RidgeRegression`	Imported
Riondato–Kornaropoulos fixed-sample betweenness approximation aka RK betweenness approximation, Riondato–Kornaropoulos betweenness sampling A fixed-sample graph betweenness approximation algorithm that chooses a sample count using a VC-dimension bound for shortest-path incidence…	Curated	Algorithms	`AIMech:RiondatoKornaropoulosBetweennessSampling`	6 claims 1 source
Ritter–Gallegos two-stage outlier-mixture fitting aka POP–BAS–OUT mixture fitting A two-stage mixture-parameter fitting procedure that estimates a regular component from a threshold-selected basic subset of a contaminated…	Curated	Algorithms	`AIMech:RitterGallegosTwoStageOutlierMixtureFitting`	4 claims 1 source
RMSprop An adaptive gradient optimization method that normalizes coordinate updates using an exponentially weighted estimate of squared gradients.	Curated	Algorithms	`AIMech:RMSprop`	1 claim 1 source
RNN Layer The base class for recurrent layers.	AIO	Layer	`AIO:RNNLayer`	Imported
RNN-NADE aka Recurrent neural network neural autoregressive distribution estimator A neural sequence architecture in which a deterministic recurrent state supplies parameters of a NADE output distribution, combining tempora…	Curated	Architectures	`AIMech:RecurrentNeuralNetworkNeuralAutoregressiveDistributionEstimator`	1 claim 2 sources
RNN-RBM aka Recurrent neural network restricted Boltzmann machine A neural sequence architecture in which a deterministic recurrent network with its own hidden state supplies parameters of a conditional RBM…	Curated	Architectures	`AIMech:RecurrentNeuralNetworkRestrictedBoltzmannMachine`	1 claim 1 source
Robust adaptive Metropolis aka RAM An adaptive random-walk Metropolis algorithm that updates the proposal shape factor by a rank-one transformation driven by the proposal dire…	Curated	Algorithms	`AIMech:RobustAdaptiveMetropolis`	1 claim 1 source
Robust continuous clustering aka RCC clustering A clustering algorithm that optimizes one representative per observation using squared data fidelity and robust attraction along a neighborh…	Curated	Algorithms	`AIMech:RobustContinuousClustering`	6 claims 5 sources
ROCK clustering aka ROCK, Robust Clustering using linKs An agglomerative clustering procedure that merges clusters using shared-neighbor link counts divided by a cluster-size normalization derived…	Curated	Algorithms	`AIMech:ROCKClustering`	1 claim 1 source
Role-author-recipient-topic model aka RART A family of message-content models in which actors have latent-role distributions and ordered sender-role/recipient-role pairs determine top…	Curated	Model Families	`AIMech:RoleAuthorRecipientTopicModel`	2 claims 1 source
SamplePairing An image-classification augmentation procedure that averages an anchor image with a randomly selected training image using equal pixel weigh…	Curated	Algorithms	`AIMech:SamplePairing`	1 claim 1 source
Sarsa aka State-action-reward-state-action An on-policy temporal-difference control algorithm that updates the current state-action value toward the observed reward plus the discounte…	Curated	Algorithms	`AIMech:Sarsa`	1 claim 2 sources
Scaled Legendre HiPPO operator aka HiPPO-LegS The HiPPO projection operator using the uniform measure over the full elapsed interval from zero to the current time, with scaled-Legendre c…	Curated	Mathematical Methods	`AIMech:HiPPOLegS`	1 claim 1 source
Scheduled sampling An autoregressive sequence-training procedure that chooses between reference and model-produced previous outputs as feedback, using a schedu…	Curated	Algorithms	`AIMech:ScheduledSampling`	6 claims 2 sources
Seasonal Autoregressive Integrated Moving-Average aka SARIMA A model that extends ARIMA, explicitly supporting univariate time series data with a seasonal component, combining seasonal differencing wit…	AIO	Model	`AIO:SeasonalAutoregressiveIntegratedMovingAverage`	Imported
SeLa aka Self-labelling via simultaneous clustering and representation learning, Self-labeling via simultaneous clustering and representation learning A self-supervised representation-learning procedure that alternates neural pseudo-label prediction and dataset-wide self-labelling through a…	Curated	Algorithms	`AIMech:SeLa`	1 claim 3 sources
Selection And Sampling Bias aka Sampling Bias, Selection Bias… A computational bias introduced by non-random selection of individuals groups or data failing to ensure representativeness.	AIO	Bias	`AIO:SelectionAndSamplingBias`	Imported
Selective Adherence Bias An individual bias characterized by the tendency to selectively adopt algorithmic advice that matches pre-existing beliefs and stereotypes.	AIO	Bias	`AIO:SelectiveAdherenceBias`	Imported
Self-supervised Learning A machine learning task that is intermediate between supervised and unsupervised learning and predicts parts of the input data from other ob…	AIO	MachineLearningTask	`AIO:SelfsupervisedLearning`	Imported
Self-Supervised LLM aka Pretext tasks A large language model which learns rich representations by solving pretext tasks that involve predicting parts of the input from other obse…	AIO	Model	`AIO:SelfSupervisedLLM`	Imported
SELU Function aka SELU, Scaled Exponential Linear Unit A mathematical function that multiplies scale (> 1) with the output of the ELU function to ensure a slope larger than one for positive input…	AIO	MathematicalFunction	`AIO:SELUFunction`	Imported
Semi-Supervised LLM aka Semi-Supervised Large Language Model, self-training A large language model which combines self-supervised pretraining on unlabeled data with supervised fine-tuning on labeled task data.	AIO	Model	`AIO:SemiSupervisedLLM`	Imported
Semidefinite Maximum Margin Clustering aka Xu2004 Maximum Margin Clustering A binary clustering procedure that relaxes latent label-equivalence matrices to a convex semidefinite program for a fixed-kernel soft-margin…	Curated	Algorithms	`AIMech:SemidefiniteMaximumMarginClustering`	4 claims 1 source
Semiparametric linear programming regression aka Semiparametric LP regression A supervised regression algorithm that jointly fits a finite kernel expansion and an unpenalized supplied parametric basis by minimizing fix…	Curated	Algorithms	`AIMech:SemiparametricLinearProgrammingRegression`	6 claims 1 source
Semiparametric support vector regression aka Semiparametric SV regression A supervised regression algorithm that jointly fits an unpenalized finite expansion of supplied basis functions and a kernel component, mini…	Curated	Algorithms	`AIMech:SemiparametricSupportVectorRegression`	7 claims 1 source
Semisupervised Semidefinite Maximum Margin Clustering aka Xu2004 Semisupervised Maximum Margin Clustering A semisupervised binary margin-learning procedure that adds observed-label pair constraints and labeled-to-unlabeled linkage constraints to…	Curated	Algorithms	`AIMech:SemisupervisedSemidefiniteMaximumMarginClustering`	6 claims 1 source
Separable Natural Evolution Strategies The Gaussian population natural evolution strategy that samples independent normal coordinates, ranks their evaluated fitness, and adapts th…	Curated	Algorithms	`AIMech:SeparableNaturalEvolutionStrategies`	6 claims 1 source
SeparableConvolution1D Layer aka SeparableConv1D Layer A convolutional layer that performs depthwise separable 1D convolution.	AIO	Layer	`AIO:SeparableConvolution1DLayer`	Imported
SeparableConvolution2D Layer aka SeparableConv2D Layer A convolutional layer that performs depthwise separable 2D convolution.	AIO	Layer	`AIO:SeparableConvolution2DLayer`	Imported
Separator-node conflict diagnostic A Bayesian graphical-model diagnostic that duplicates a selected separator node or node vector, partitions the information informing it, and…	Curated	Algorithms	`AIMech:SeparatorNodeConflictDiagnostic`	7 claims 1 source
Sequential Model-based Algorithm Configuration aka SMAC A sequential algorithm-configuration procedure that uses random-forest performance models to propose parameter settings and compares candida…	Curated	Algorithms	`AIMech:SequentialModelBasedAlgorithmConfiguration`	1 claim 1 source
Set Transformer A neural encoder-decoder architecture for permutation-invariant set-input prediction that uses attention to encode interactions among elemen…	Curated	Architectures	`AIMech:SetTransformer`	1 claim 1 source
Set Transformer++ aka ST++ A Set Transformer architecture revision that replaces its induced-attention encoder blocks with set-normalized blocks retaining identity res…	Curated	Architectures	`AIMech:SetTransformerPlusPlus`	1 claim 1 source
Shake-Shake regularization The original residual-network training and inference procedure that combines two learned branch outputs with complementary uniform random we…	Curated	Algorithms	`AIMech:ShakeShakeRegularization`	6 claims 1 source
ShakeDrop regularization A residual-network regularization procedure that uses a Bernoulli switch to alternate ordinary residual computation with separately specifie…	Curated	Algorithms	`AIMech:ShakeDropRegularization`	6 claims 2 sources
SHapley additive explanations aka SHAP An additive feature-attribution framework assigning Shapley values to a prediction through a specified function for evaluating feature subse…	Curated	Mathematical Methods	`AIMech:SHAP`	1 claim 1 source
Shared inverse-lengthscale variational sparse-spectrum inference The Tan–Ong–Nott–Jasra sparse-spectrum regression inference procedure that alternates a Gaussian nonconjugate variational proposal for a sha…	Curated	Algorithms	`AIMech:SharedInverseLengthscaleVariationalSparseSpectrumInference`	7 claims 2 sources
Sigmoid belief network aka SBN A directed acyclic probabilistic network of binary variables whose forward conditional probabilities are logistic functions of weighted pare…	Curated	Architectures	`AIMech:SigmoidBeliefNetwork`	1 claim 1 source
Sigmoid Function aka tore A mathematical function that applies the sigmoid activation function sigmoid(x) = 1 / (1 + exp(-x)) always returning a value between 0 and 1…	AIO	MathematicalFunction	`AIO:SigmoidFunction`	Imported
SimCLR aka Simple framework for contrastive learning of visual representations A self-supervised representation-learning procedure that jointly trains an encoder and a nonlinear projection head by contrasting two augmen…	Curated	Algorithms	`AIMech:SimCLR`	1 claim 1 source
SimNet aka SimNets A neural architecture family built from learned template-similarity operations and MEX log-mean-exp operations that combine shifted similari…	Curated	Architectures	`AIMech:SimNet`	8 claims 2 sources
Simple recursive best-first search aka SRBFS A recursive best-first search procedure that initializes generated children from their static evaluation values, explores the best child wit…	Curated	Algorithms	`AIMech:SimpleRecursiveBestFirstSearch`	2 claims 2 sources
SimpleRNN Layer A recurrent layer that implements a fully-connected RNN where the output is to be fed back to input.	AIO	Layer	`AIO:SimpleRNNLayer`	Imported
SimpleRNNCell Layer A layer that processes one step within the whole time sequence input for a SimpleRNN layer.	AIO	Layer	`AIO:SimpleRNNCellLayer`	Imported
Simplified memory-bounded A-star search aka SMA* A node-budgeted best-first tree-search algorithm that generates one successor at a time, propagates evaluation values through pathmax and co…	Curated	Algorithms	`AIMech:SimplifiedMemoryBoundedAStar`	4 claims 1 source
Simpson's Paradox Bias aka Simpson's Paradox A selection and sampling bias where the association between two variables changes when controlling for another variable.	AIO	Bias	`AIO:SimponsParadoxBias`	Imported
SimSiam A self-supervised representation-learning procedure that trains a shared encoder and predictor to match the encoder output of another augmen…	Curated	Algorithms	`AIMech:SimSiam`	1 claim 1 source
Simulated annealing A stochastic optimization procedure that explores candidate configurations with temperature-controlled acceptance of cost-increasing moves a…	Curated	Algorithms	`AIMech:SimulatedAnnealing`	2 claims 2 sources
Single-step parametric maxT inference A simultaneous-inference procedure for a declared family of linear functions of model parameters that standardizes joint estimates and uses…	Curated	Algorithms	`AIMech:SingleStepParametricMaxTInference`	7 claims 1 source
Slice sampling An auxiliary-variable Monte Carlo method that augments a target density with a uniform height below its graph and updates the state using a…	Curated	Algorithms	`AIMech:SliceSampling`	1 claim 1 source
Smart Augmentation A learned augmentation procedure that trains a network to synthesize examples from same-class inputs while receiving both a within-class ref…	Curated	Algorithms	`AIMech:SmartAugmentation`	1 claim 1 source
SmoothGrad A sensitivity-map smoothing method that averages maps computed on Gaussian-noise perturbations of an input.	Curated	Algorithms	`AIMech:SmoothGrad`	1 claim 1 source
SMOTE-NC The original mixed nominal/continuous extension of SMOTE that synthesizes minority-class training examples by finding minority neighbors wit…	Curated	Preprocessing Methods	`AIMech:SMOTENC`	6 claims 1 source
Societal Bias A systemic bias characterized by being for or against groups or individuals based on social identities demographic factors or immutable phys…	AIO	Bias	`AIO:SocietalBias`	Imported
Soft actor-critic aka SAC An off-policy actor-critic algorithm fitting a stochastic policy and soft value functions under a reward-plus-policy-entropy objective.	Curated	Algorithms	`AIMech:SoftActorCritic`	1 claim 1 source
Soft Q-learning The 2017 maximum-entropy continuous-control learning algorithm that fits neural soft action values from replayed transitions and trains an a…	Curated	Algorithms	`AIMech:SoftQLearning`	6 claims 3 sources
Softmax Function A mathematical function where the elements of the output vector are in range (0 1) and sum to 1 and each vector is handled independently.	AIO	MathematicalFunction	`AIO:SoftmaxFunction`	Imported
Softmax Layer An activation layer that applies the softmax function to the inputs.	AIO	Layer	`AIO:SoftmaxLayer`	Imported
Softplus Function A mathematical function that is softplus(x) = log(exp(x) + 1).	AIO	MathematicalFunction	`AIO:SoftplusFunction`	Imported
Softsign Function A mathematical function that is softsign(x) = x / (abs(x) + 1).	AIO	MathematicalFunction	`AIO:SoftsignFunction`	Imported
Space-Alternating Generalized Expectation Maximization aka SAGE Algorithm, Space-Alternating GEM A generalized expectation-maximization method that updates selected parameter blocks using block-specific hidden-data spaces or valid object…	Curated	Algorithms	`AIMech:SpaceAlternatingGeneralizedExpectationMaximization`	4 claims 3 sources
Sparse additive generative model aka SAGE A generative model family for categorical text data that forms word probabilities by normalizing a background log-frequency vector plus spar…	Curated	Model Families	`AIMech:SparseAdditiveGenerativeModel`	1 claim 1 source
Sparse Auto Encoder aka SAE, Sparse AE… An autoencoder network with more hidden units than inputs that constrains only a few hidden units to be active at once.	AIO	Network	`AIO:SparseAutoEncoder`	Imported
Sparse Expectation Maximization aka Sparse EM An EM variant that updates relative latent-state probabilities within selected plausible sets while preserving their total mass and all outs…	Curated	Algorithms	`AIMech:SparseExpectationMaximization`	3 claims 1 source
Sparse Learning aka Sparse coding, Sparse dictionary Learning A representation learning network that finds sparse representations of input data as a linear combination of basic elements and identifies t…	AIO	Network	`AIO:SparseLearning`	Imported
Sparse LLM aka Sparse Large Language Model, model compression… A large language model that uses techniques like pruning or quantization to reduce the number of non-zero parameters in the model making it…	AIO	Model	`AIO:SparseLLM`	Imported
Sparse pachinko allocation inference aka pruned PAM Gibbs sampling An approximate pachinko-allocation fitting procedure that restricts token path resampling to currently active document topics and word-assoc…	Curated	Algorithms	`AIMech:SparsePachinkoAllocationInference`	3 claims 1 source
Sparse-spectrum Gaussian-process exact moment matching aka SSGP-EMM An uncertain-input prediction algorithm that analytically integrates sine/cosine feature moments of a fixed sparse-spectrum Gaussian-process…	Curated	Algorithms	`AIMech:SparseSpectrumGaussianProcessExactMomentMatching`	5 claims 3 sources
Sparse-spectrum Gaussian-process linearized uncertain-input prediction aka SSGP-Lin A local uncertain-input prediction algorithm for a fixed sparse-spectrum Gaussian-process posterior that linearizes the posterior mean at th…	Curated	Algorithms	`AIMech:SparseSpectrumGaussianProcessLinearizedPrediction`	5 claims 4 sources
Sparse-spectrum Gaussian-process regression aka SSGP, Sparse spectrum Gaussian process A Gaussian-process regression model family whose latent prior is a finite sum of paired sine and cosine features with independent Gaussian c…	Curated	Model Families	`AIMech:SparseSpectrumGaussianProcessRegression`	6 claims 2 sources
Spatial Regression A regression analysis used to model spatial relationships.	AIO	MachineLearningTask	`AIO:SpatialRegression`	Imported
Spatial Transformer aka Spatial Transformer module A learnable neural-network component that predicts an input-dependent spatial transformation and uses the resulting sampling grid to warp an…	Curated	Layers & Modules	`AIMech:SpatialTransformer`	2 claims 2 sources
SpatialDropout1D Layer A regularization layer that performs the same function as Dropout but drops entire 1D feature maps instead of individual elements.	AIO	Layer	`AIO:SpatialDropout1DLayer`	Imported
SpatialDropout2D Layer A regularization layer that performs the same function as Dropout but drops entire 2D feature maps instead of individual elements.	AIO	Layer	`AIO:SpatialDropout2DLayer`	Imported
SpatialDropout3D Layer A regularization layer that performs the same function as Dropout but drops entire 3D feature maps instead of individual elements.	AIO	Layer	`AIO:SpatialDropout3DLayer`	Imported
Speaker-Adaptive Training LHUC aka SAT-LHUC An acoustic-model training procedure that jointly learns shared network parameters, training-speaker hidden-unit contribution transforms and…	Curated	Algorithms	`AIMech:SpeakerAdaptiveTrainingLHUC`	5 claims 1 source
Speaker-Dependent Pooling Adaptation An acoustic-model adaptation procedure that updates a small set of pooling parameters for a target speaker using decoded acoustic targets wh…	Curated	Algorithms	`AIMech:SpeakerDependentPoolingAdaptation`	5 claims 1 source
Spectral hashing An unsupervised binary-code learning algorithm that approximates a spectral similarity-preservation objective using a PCA-aligned rectangula…	Curated	Algorithms	`AIMech:SpectralHashing`	1 claim 1 source
Spiking Hidden Layer A hidden layer that makes connections to an additional, heterogeneous hidden layer; modeled after biological neural networks.	AIO	Layer	`AIO:SpikingHiddenLayer`	Imported
Square root graphical model aka SQR, Square root Markov random field A family of finite undirected graphical probability models that retains univariate base measures while coupling specified square roots of su…	Curated	Model Families	`AIMech:SquareRootGraphicalModel`	1 claim 2 sources
Squeeze-and-Excitation block aka SE block A neural-network feature recalibration component that globally averages each channel, transforms the resulting descriptor through a learned…	Curated	Layers & Modules	`AIMech:SqueezeAndExcitationBlock`	1 claim 1 source
Stack-augmented recurrent neural network aka Stack RNN A recurrent sequence architecture whose neural controller reads the leading entries of one or more external stack states and learns continuo…	Curated	Architectures	`AIMech:StackAugmentedRecurrentNeuralNetwork`	6 claims 3 sources
StackedRNNCells Layer A layer that allows a stack of RNN cells to behave as a single cell.	AIO	Layer	`AIO:StackedRNNCellsLayer`	Imported
Stacking aka Stacked generalization Ensemble learning that trains a final estimator on base-estimator predictions.	Curated	Algorithms	`AIMech:Stacking`	1 claim 1 source
Stein variational gradient descent An interacting-particle inference algorithm that approximates a differentiable continuous target by synchronously transporting particles wit…	Curated	Algorithms	`AIMech:SteinVariationalGradientDescent`	5 claims 3 sources
Stein Variational Policy Gradient aka SVPG A policy optimization method that applies Stein variational gradient descent to an entropy-regularized distribution over policy parameters,…	Curated	Algorithms	`AIMech:SteinVariationalPolicyGradient`	6 claims 2 sources
Stepping-out slice sampling A univariate slice-sampling algorithm that randomly places a width-w interval around the current point, expands it in width-w steps under a…	Curated	Algorithms	`AIMech:SteppingOutSliceSampling`	1 claim 1 source
Stigmergy A computational coordination mechanism in which actions modify an accessible environment or medium and those changes influence subsequent ac…	Curated	Coordination Mechanisms	`AIMech:Stigmergy`	5 claims 2 sources
Stochastic Approximation Expectation Maximization aka SAEM, Stochastic Approximation EM An incomplete-data fitting method that recursively averages simulated complete-data log objectives or sufficient statistics using a step-siz…	Curated	Algorithms	`AIMech:StochasticApproximationExpectationMaximization`	4 claims 2 sources
Stochastic beam search aka SBS The sequence-sampling algorithm of Kool, van Hoof and Welling that implements Gumbel-Top-k without replacement implicitly on a locally norma…	Curated	Algorithms	`AIMech:StochasticBeamSearch`	3 claims 2 sources
Stochastic depth A residual-network training procedure that randomly bypasses residual transformations during training and uses all residual transformations…	Curated	Algorithms	`AIMech:StochasticDepth`	1 claim 1 source
Stochastic Expectation Maximization aka Stochastic EM, SEM (stochastic expectation maximization) A finite-mixture fitting algorithm that draws one hard component assignment for each observation from its current posterior responsibilities…	Curated	Algorithms	`AIMech:StochasticExpectationMaximization`	4 claims 2 sources
Stochastic factorized variational sparse-spectrum Gaussian-process inference aka sfVSSGP The Gal–Turner stochastic extension of factorized variational sparse-spectrum regression that estimates its full-data evidence lower bound w…	Curated	Algorithms	`AIMech:StochasticFactorizedVariationalSparseSpectrumGaussianProcessInference`	5 claims 3 sources
Stochastic gradient descent aka SGD Optimization using gradients estimated from sampled training observations.	Curated	Algorithms	`AIMech:StochasticGradientDescent`	1 claim 1 source
Stochastic learning automata A family of adaptive stochastic decision procedures that selects an action from a maintained finite action-probability vector, receives eval…	Curated	Learning Paradigms	`AIMech:StochasticLearningAutomata`	6 claims 1 source
Stochastic local search A configurable family of combinatorial search algorithms that initializes a search position and any memory, then applies a specified neighbo…	Curated	Algorithms	`AIMech:StochasticLocalSearch`	6 claims 2 sources
Stochastic nonconjugate GLMM variational inference A finite-population Bayesian GLMM inference procedure that iterates selected cluster-local Gaussian factors and uses expanded cluster miniba…	Curated	Algorithms	`AIMech:StochasticNonconjugateGLMMVariationalInference`	7 claims 2 sources
Stochastic Pooling A spatial neural pooling layer that samples one activation per region with probability proportional to its nonnegative value during training…	Curated	Layers & Modules	`AIMech:StochasticPooling`	5 claims 1 source
Stochastic-times-smooth unit aka STS unit A stochastic activation that sets p=sigmoid(a), samples a Bernoulli gate with success probability sqrt(p), and outputs the gate multiplied b…	Curated	Mathematical Methods	`AIMech:StochasticTimesSmoothUnit`	1 claim 1 source
Straight-through estimator aka ST estimator, Identity straight-through estimator A surrogate-gradient rule that keeps a hard threshold or sampled binary output in the forward computation while propagating its downstream d…	Curated	Mathematical Methods	`AIMech:StraightThroughEstimator`	3 claims 1 source
Straight-through Gumbel-Softmax estimator aka ST Gumbel-Softmax, ST Gumbel estimator A surrogate-gradient estimator that uses a hard one-hot argmax of a Gumbel-Softmax sample in the forward computation and substitutes the cor…	Curated	Mathematical Methods	`AIMech:StraightThroughGumbelSoftmax`	2 claims 1 source
Strategic oscillation A search-control strategy that alternates search directions or regimes around selected boundaries, controlling excursions and returns to exp…	Curated	Algorithms	`AIMech:StrategicOscillation`	1 claim 2 sources
Streetlight Effect Bias aka Streetlight Effect An individual bias where people search only where it is easiest to look.	AIO	Bias	`AIO:StreetlightEffectBias`	Imported
StringLookup Layer A categorical features preprocessing layer that maps string features to integer indices.	AIO	Layer	`AIO:StringLookupLayer`	Imported
STRIPS planning method A symbolic planning method that uses means–ends analysis and theorem proving over world models to construct a sequence of operators satisfyi…	Curated	Algorithms	`AIMech:STRIPSPlanning`	1 claim 1 source
Structurally constrained recurrent neural network aka SCRN, SCRNN A recurrent sequence architecture coupling a nonlinear recurrent hidden state with a separate linear context state whose recurrence is const…	Curated	Architectures	`AIMech:StructurallyConstrainedRecurrentNeuralNetwork`	6 claims 5 sources
Structured mean-field inference aka Structured mean-field approximation A variational inference method that approximates a target distribution with a tractable family retaining selected dependencies, choosing its…	Curated	Mathematical Methods	`AIMech:StructuredMeanFieldInference`	1 claim 1 source
Structured state space sequence model aka S4 A structured linear state-space sequence model whose normal-plus-low-rank state matrix is transformed to diagonal-plus-low-rank form for eff…	Curated	Model Families	`AIMech:S4`	1 claim 1 source
Structured variational inference for factorial HMMs aka Structured mean-field inference for factorial HMMs A variational inference procedure for factorial hidden Markov models that approximates the posterior by independent chain-path distributions…	Curated	Algorithms	`AIMech:StructuredVariationalInferenceForFactorialHMMs`	1 claim 1 source
Sub-Cluster Component clustering aka Sub-Cluster Component algorithm An agglomerative clustering algorithm that repeatedly merges weakly connected components of a thresholded nearest-neighbor graph over the cu…	Curated	Algorithms	`AIMech:SubClusterComponentClustering`	7 claims 1 source
Sublinear Poisson graphical model aka SPGM, Sublinear Poisson Markov random field A finite-graph model for unbounded nonnegative integer counts that retains factorial base measures while replacing counts in unary and pairw…	Curated	Model Families	`AIMech:SublinearPoissonGraphicalModel`	1 claim 2 sources
Submodular pick LIME aka SP-LIME A method selecting a budgeted set of local LIME explanations by greedily increasing weighted coverage of explanatory features.	Curated	Algorithms	`AIMech:SPLIME`	1 claim 1 source
Subtract Layer A merging layer that subtracts two inputs.	AIO	Layer	`AIO:SubtractLayer`	Imported
Subword Segmentation aka Fragmentation, Part-word Division… A data preparation that divides text into subword units which are smaller than words but larger than individual characters to improve the ef…	AIO	Preprocessing	`AIO:SubwordSegmentation`	Imported
Successive Halving aka SHA, Sequential Halving A staged best-candidate selection algorithm that divides a resource budget across elimination rounds, evaluates surviving candidates with co…	Curated	Algorithms	`AIMech:SuccessiveHalving`	1 claim 2 sources
Sunk Cost Fallacy Bias aka Sunk Cost Fallacy A bias characterized by the tendency to continue an endeavor due to previously invested resources despite costs outweighing benefits.	AIO	Bias	`AIO:SunkCostFallacyBias`	Imported
Supervised Biclustering aka Supervised Block Clustering, Supervised Co-clustering… A biclustering task focused on methods that simultaneously cluster the rows and columns of a labeled matrix considering data labels to enhan…	AIO	MachineLearningTask	`AIO:SupervisedBiclustering`	Imported
Supervised Clustering aka Supervised Cluster Analysis A clustering focused on methods that group labeled objects such that objects in the same group have similar labels relative to those in othe…	AIO	MachineLearningTask	`AIO:SupervisedClustering`	Imported
Supervised Learning A machine learning task focused on methods that learn a function mapping input to output based on example input-output pairs.	AIO	MachineLearningTask	`AIO:SupervisedLearning`	Imported
Supervised Principal Components aka Supervised Principal Components Regression A prediction procedure that screens features by their marginal association with an outcome, computes principal components of the retained fe…	Curated	Algorithms	`AIMech:SupervisedPrincipalComponents`	4 claims 1 source
Supplemented Expectation Conditional Maximization aka Supplemented ECM, SECM A numerical supplement to expectation conditional maximization that recovers observed-data asymptotic parameter covariance from expected com…	Curated	Algorithms	`AIMech:SupplementedExpectationConditionalMaximization`	4 claims 1 source
Supplemented Expectation Maximization aka Supplemented EM, SEM Algorithm (Supplemented EM) A numerical supplement to expectation maximization that combines expected complete-data information with the local Jacobian of the EM update…	Curated	Algorithms	`AIMech:SupplementedExpectationMaximization`	3 claims 1 source
Support Vector Clustering aka SVC An unsupervised clustering procedure that fits a soft enclosing sphere to observations in Gaussian-kernel feature space, then labels retaine…	Curated	Algorithms	`AIMech:SupportVectorClustering`	7 claims 1 source
Support vector data description aka SVDD, Support vector domain description… A one-class support-estimation algorithm that learns a sphere in an input or kernel feature space by minimizing squared radius plus linearly…	Curated	Algorithms	`AIMech:SupportVectorDataDescription`	6 claims 3 sources
Support Vector Machine aka SVM, SVN… A network with supervised learning models for classification and regression that maps training examples to points in space maximizing the ga…	AIO	Network	`AIO:SupportVectorMachine`	Imported
Survival Analysis A machine learning task focused on methods for analyzing the expected duration of time until one or more events occur such as death in biolo…	AIO	MachineLearningTask	`AIO:SurvivalAnalysis`	Imported
Survivorship Bias A processing bias characterized by the tendency to focus on items observations or people that "survive" a selection process overlooking thos…	AIO	Bias	`AIO:SurvivorshipBias`	Imported
Swapout A stochastic neural-network training and inference procedure that forms elementwise Bernoulli-selected sums of already computed compatible t…	Curated	Algorithms	`AIMech:Swapout`	6 claims 1 source
Swarm intelligence A computational design paradigm, in the broadened 1999 formulation, that develops algorithms or distributed problem-solving devices inspired…	Curated	Computational Paradigms	`AIMech:SwarmIntelligence`	5 claims 1 source
SwAV aka Swapping assignments between views An online self-supervised visual representation-learning procedure that predicts soft prototype assignments of one augmented image view from…	Curated	Algorithms	`AIMech:SwAV`	1 claim 2 sources
Swish Function A mathematical function that is x*sigmoid(x) a smooth non-monotonic function that consistently matches or outperforms ReLU on deep networks.	AIO	MathematicalFunction	`AIO:SwishFunction`	Imported
Symmetric delayed rejection aka Symmetric delaying rejection algorithm The delayed-rejection specialization using the same symmetric proposal kernel at every stage, centered through the last rejected candidate,…	Curated	Algorithms	`AIMech:SymmetricDelayedRejection`	1 claim 1 source
Symmetrically Connected Network aka SCN A network that is a type of recurrent neural network where connections between units are symmetrical with equal weights in both directions.	AIO	Network	`AIO:SymmetricallyConnectedNetwork`	Imported
SyncBatchNorm Layer aka SyncBatchNorm A batch normalization layer that applies synchronous Batch Normalization across multiple devices.	AIO	Layer	`AIO:SyncBatchNormLayer`	Imported
Synthetic Minority Over-sampling Technique aka SMOTE A minority-class oversampling method that generates synthetic labeled feature vectors by interpolating between an observed minority example…	Curated	Preprocessing Methods	`AIMech:SyntheticMinorityOversamplingTechnique`	1 claim 1 source
Systemic Bias A bias resulting from procedures and practices of systems that operate in ways which result in certain social groups being advantaged or fav…	AIO	Bias	`AIO:SystemicBias`	Imported
t-Distributed Stochastic Neighbor embedding aka t-SNE, tSNE A dimensionality reduction for visualizing high-dimensional data by giving each datapoint a location in a two or three-dimensional map.	AIO	MachineLearningTask	`AIO:tDistributedStochasticNeighborembedding`	Imported
T-Few Fine-Tuning aka T-Few A few-shot classification fine-tuning recipe that adapts a pretrained T0 model through IA3 activation vectors, multitask pretraining of thos…	Curated	Algorithms	`AIMech:TFewFineTuning`	5 claims 2 sources
Tabu search aka TS A memory-guided optimization framework that steers a search trajectory by making selected moves temporarily inadmissible from search history…	Curated	Algorithms	`AIMech:TabuSearch`	1 claim 1 source
Tabu search for SAT (TSAT) The SAT-specific basic tabu-search method described by Mazure, Saïs and Grégoire in 1997, which systematically excludes recently flipped var…	Curated	Algorithms	`AIMech:TabuSearchForSAT`	5 claims 2 sources
Tanh Function aka hyperbolic tangent A mathematical function that is the hyperbolic tangent activation function.	AIO	MathematicalFunction	`AIO:TanhFunction`	Imported
Taylor approximation for uncertain-input Gaussian-process prediction aka Taylor Gaussian-process uncertainty propagation A local Gaussian-process prediction algorithm that expands a fixed posterior mean to first order and its latent variance to second order abo…	Curated	Algorithms	`AIMech:GaussianProcessTaylorUncertainInputPrediction`	5 claims 3 sources
Teacher forcing A sequence-training procedure that supplies reference outputs from earlier steps as feedback for subsequent predictions, in place of the mod…	Curated	Algorithms	`AIMech:TeacherForcing`	6 claims 2 sources
Tempered expectation maximization aka Tempered EM An entropy-tempered generalization of expectation maximization for finite latent-state models that alternates powered latent-joint responsib…	Curated	Algorithms	`AIMech:TemperedExpectationMaximization`	1 claim 1 source
Tempered transitions aka Neal tempered transitions A Markov chain Monte Carlo transition algorithm that proposes a new target state through a prescribed outward and return sequence of mutuall…	Curated	Algorithms	`AIMech:TemperedTransitions`	6 claims 2 sources
Temporal Bias A selection and sampling bias arising from differences in populations and behaviors over time.	AIO	Bias	`AIO:TemporalBias`	Imported
Temporal ensembling A semi-supervised classifier-training procedure that regularizes a current stochastic prediction toward a bias-corrected exponential average…	Curated	Algorithms	`AIMech:TemporalEnsembling`	1 claim 2 sources
Temporal factored restricted Boltzmann machine language model aka Temporal FRBM A sequential extension of the factored RBM language model that directs information from the preceding binary hidden state into the current h…	Curated	Architectures	`AIMech:TemporalFactoredRestrictedBoltzmannMachineLanguageModel`	1 claim 2 sources
Temporal restricted Boltzmann machine aka TRBM A neural sequence architecture that multiplies time-indexed conditional RBM distributions whose visible and hidden biases depend on precedin…	Curated	Architectures	`AIMech:TemporalRestrictedBoltzmannMachine`	1 claim 2 sources
Temporal-difference learning aka TD learning A family of prediction-learning methods that assign temporal credit using discrepancies between successive, recursively related predictions…	Curated	Learning Paradigms	`AIMech:TemporalDifferenceLearning`	2 claims 2 sources
Temporal-kernel recurrent neural network aka TKRNN A recurrent architecture that factors connections across time into learned spatial weights and source-specific exponential temporal kernels,…	Curated	Architectures	`AIMech:TemporalKernelRecurrentNeuralNetwork`	6 claims 1 source
Text Preprocessing Layer A layer that performs text data preprocessing operations.	AIO	Layer	`AIO:TextPreprocessingLayer`	Imported
TextVectorization Layer A text preprocessing layer that maps text features to integer sequences.	AIO	Layer	`AIO:TextVectorizationLayer`	Imported
Threshold Autoregressive aka TAR A model that allows for different autoregressive processes depending on the regime or state of the time series, enabling the capture of nonl…	AIO	Model	`AIO:ThresholdAutoregressive`	Imported
ThresholdedReLU Layer An activation layer that applies the thresholded rectified linear unit function element-wise.	AIO	Layer	`AIO:ThresholdedReLULayer`	Imported
Time Series Analysis A machine learning task focused on methods for analyzing time series data to extract meaningful statistics and characteristics.	AIO	MachineLearningTask	`AIO:TimeSeriesAnalysis`	Imported
Time Series Forecasting A machine learning task focused on methods that predict future values based on previously observed values.	AIO	MachineLearningTask	`AIO:TimeSeriesForecasting`	Imported
TimeDistributed Layer A recurrent layer that applies a layer to every temporal slice of an input.	AIO	Layer	`AIO:TimeDistributedLayer`	Imported
Tokenization aka Lexical Analysis, Text Segmentation A data preparation that converts a sequence of text into smaller meaningful units called tokens typically words or subwords for the purpose…	AIO	Preprocessing	`AIO:Tokenization`	Imported
Topic-model evocation score aka Top-m evocation metric A topic-model evaluation method that orders judged word pairs by model-derived weights and sums their human evocation ratings over a chosen…	Curated	Evaluation Methods	`AIMech:TopicModelEvocationScore`	2 claims 2 sources
Topical n-gram model aka TNG A topic-conditioned sequence model that chooses whether each word uses a topic-specific unigram distribution or a topic-and-previous-word bi…	Curated	Model Families	`AIMech:TopicalNGramModel`	2 claims 1 source
Topics over Time model aka TOT A topic-model family combining fixed topic-word distributions with topic-specific continuous timestamp densities, so that words and their ob…	Curated	Model Families	`AIMech:TopicsOverTimeModel`	2 claims 1 source
Topographic Independent Component Analysis aka Topographic ICA, TICA A linear latent-component model whose otherwise conditionally independent source components share random scales through fixed overlapping ne…	Curated	Model Families	`AIMech:TopographicICA`	4 claims 1 source
Tractable unnormalized Barber–Agakov bound aka TUBA, TUBA bound A tractable unnormalized Barber–Agakov lower-bound parameterization that uses a real critic and a positive output-dependent normalizer to re…	Curated	Mathematical Methods	`AIMech:TUBABound`	2 claims 2 sources
Training signal annealing aka TSA A supervised-loss scheduling procedure that temporarily excludes labeled examples already predicted with confidence above an increasing thre…	Curated	Algorithms	`AIMech:TrainingSignalAnnealing`	1 claim 3 sources
TrainingStrategy aka Instructional Methods, Learning Techniques A preprocessing used to train machine learning models including techniques such as supervised learning unsupervised learning reinforcement l…	AIO	TrainingStrategy	`AIO:TrainingStrategy`	Imported
Transfer Learning A machine learning task focused on methods that reuse or transfer information from previously learned tasks to facilitate the learning of ne…	AIO	MachineLearningTask	`AIO:TransferLearning`	Imported
Transfer Learning LLM aka Transfer LLM, transfer learning A large language model that leverages knowledge acquired during training on one task to improve performance on different but related tasks f…	AIO	Model	`AIO:TransferLearningLLM`	Imported
Transformer Language Model aka Transformer LM A language model that uses the transformer architecture based on multi-head attention mechanisms allowing it to contextualize tokens within…	AIO	Model	`AIO:TransformerLanguageModel`	Imported
Transformer LLM aka Transformer Large Language Model A transformer language model with large training corpuses and sets of parameters that uses the transformer architecture based on multi-head…	AIO	Model	`AIO:TransformerLLM`	Imported
Transformer Network A deep neural network that utilizes attention mechanisms to weigh the significance of input data.	AIO	Network	`AIO:TransformerNetwork`	Imported
Transforming autoencoder A deterministic neural architecture that learns first-level capsules from images, transformed target images and supplied transformations. Ea…	Curated	Architectures	`AIMech:TransformingAutoencoder`	6 claims 1 source
Tree SHAP A tree-specific algorithm computing Shapley feature attributions through recursive bookkeeping of weighted feature subsets along decision pa…	Curated	Algorithms	`AIMech:TreeSHAP`	2 claims 2 sources
Tree-size estimation by partial backtracking aka Purdom partial-backtracking estimator A randomized backtracking-tree estimator that explores a uniformly selected subset of successors at each visited branching point and uses in…	Curated	Algorithms	`AIMech:PartialBacktrackingTreeEstimation`	5 claims 1 source
Tree-structured Parzen Estimator aka TPE, Tree-structured Parzen Estimator Approach A sequential hyperparameter optimization method that separates observations by a loss quantile, fits tree-structured densities for the bette…	Curated	Algorithms	`AIMech:TreeStructuredParzenEstimator`	1 claim 1 source
TriMap A nonlinear dimensionality-reduction algorithm that selects weighted triplet comparisons from high-dimensional data and optimizes embedding…	Curated	Algorithms	`AIMech:TriMap`	2 claims 2 sources
Triplet Markov chain aka TMC A latent-variable sequence-model family that introduces an auxiliary process so that the joint hidden, auxiliary and observed process is fir…	Curated	Model Families	`AIMech:TripletMarkovChain`	1 claim 1 source
Triplet Markov field aka TMF A latent-variable spatial-model family that introduces an auxiliary field so the complete hidden, auxiliary and observed triplet has a norma…	Curated	Model Families	`AIMech:TripletMarkovField`	1 claim 1 source
True online GTD(lambda) A linear off-policy state-value prediction algorithm that couples two Dutch eligibility traces with an accumulating gradient-correction trac…	Curated	Algorithms	`AIMech:TrueOnlineGTDLambda`	6 claims 1 source
True online Sarsa(lambda) A linear on-policy action-value control algorithm that combines a Dutch eligibility trace with a correction for changing predictions, using…	Curated	Algorithms	`AIMech:TrueOnlineSarsaLambda`	6 claims 2 sources
True online TD(lambda) A linear temporal-difference policy-evaluation algorithm that combines a Dutch eligibility trace with a correction for changing predictions,…	Curated	Algorithms	`AIMech:TrueOnlineTDLambda`	6 claims 2 sources
Truncated Poisson graphical model aka TPGM, Truncated Poisson Markov random field A finite pairwise count graphical model with a fixed upper count limit, factorial base measures and Poisson-kernel full conditionals renorma…	Curated	Model Families	`AIMech:TruncatedPoissonGraphicalModel`	1 claim 2 sources
Trust region policy optimization aka TRPO A policy-optimization method that optimizes a surrogate objective while constraining the change in policy by a trust region based on Kullbac…	Curated	Algorithms	`AIMech:TrustRegionPolicyOptimization`	1 claim 1 source
Two-stage adaptive-neighborhood sparse-spectrum regression A query-specific sparse-spectrum regression procedure that fits a variational model to Euclidean neighbors, reselects neighbors from the ful…	Curated	Algorithms	`AIMech:TwoStageAdaptiveNeighborhoodSparseSpectrumRegression`	5 claims 1 source
UMAP aka Uniform Manifold Approximation and Projection, Uniform Manifold Approximation and Projection for Dimension Reduction A nonlinear embedding algorithm that constructs a locally scaled, symmetrized nearest-neighbor similarity graph and places its vertices in a…	Curated	Algorithms	`AIMech:UMAP`	3 claims 3 sources
Unadjusted Langevin algorithm aka ULA An approximate sampling algorithm that discretizes overdamped Langevin dynamics by an explicit gradient drift and Gaussian noise without a M…	Curated	Algorithms	`AIMech:UnadjustedLangevinAlgorithm`	2 claims 2 sources
Uncertainty Bias A selection and sampling bias favoring groups better represented in training data due to less prediction uncertainty.	AIO	Bias	`AIO:UncertaintyBias`	Imported
UnitNormalization Layer A recurrent layer that normalizes a batch of inputs so that each input in the batch has a L2 norm equal to 1.	AIO	Layer	`AIO:UnitNormalizationLayer`	Imported
Univariate marginal distribution algorithm The original unsmoothed binary population optimizer that selects a nonempty set of evaluated bit strings, replaces each coordinate probabili…	Curated	Algorithms	`AIMech:UnivariateMarginalDistributionAlgorithm`	6 claims 2 sources
Unsupervised Biclustering aka Unsupervised Block Clustering, Unsupervised Co-clustering… A biclustering task focused on methods that simultaneously cluster the rows and columns of an unlabeled input matrix to identify submatrices…	AIO	MachineLearningTask	`AIO:UnsupervisedBiclustering`	Imported
Unsupervised Clustering aka Unsupervised Cluster Analysis A clustering focused on methods that group a set of unlabeled objects such that objects in the same group are more similar to each other tha…	AIO	MachineLearningTask	`AIO:UnsupervisedClustering`	Imported
Unsupervised Data Augmentation aka UDA A semi-supervised classifier-training procedure that combines labeled prediction loss with consistency between fixed current-model predictio…	Curated	Algorithms	`AIMech:UnsupervisedDataAugmentation`	1 claim 5 sources
Unsupervised Learning A machine learning task focused on algorithms that learn patterns from unlabeled data.	AIO	MachineLearningTask	`AIO:UnsupervisedLearning`	Imported
Unsupervised LLM aka Unsupervised Large Language Model, self-supervised A large language model that is trained solely on unlabeled data using self-supervised objectives like masked language modeling without any s…	AIO	Model	`AIO:UnsupervisedLLM`	Imported
Unsupervised Pretrained Network aka UPN A network that initializes a discriminative neural net from one trained using an unsupervised criterion.	AIO	Network	`AIO:UnsupervisedPretrainedNetwork`	Imported
Unweighted Multiview Convex Mixture Clustering aka Multiview Convex Mixture Model Clustering, Convex Mixture Models for Multi-view Clustering A multiview exemplar-clustering procedure that fits a single vector of exemplar weights by minimizing the equally weighted sum of fixed-comp…	Curated	Algorithms	`AIMech:UnweightedMultiviewConvexMixtureClustering`	3 claims 1 source
UpSampling1D Layer A reshaping layer that upsamples the input by repeating each temporal step size times along the time axis.	AIO	Layer	`AIO:UpSampling1DLayer`	Imported
UpSampling2D Layer A layer that upsamples the input by repeating each row and column size times.	AIO	Layer	`AIO:UpSampling2DLayer`	Imported
UpSampling3D Layer A layer that upsamples the input by repeating each depth, height and width size times.	AIO	Layer	`AIO:UpSampling3DLayer`	Imported
Upward-downward nested antithetic mixture A finite conditional Markov update that chooses with equal probability between complete upward and downward nested antithetic modification k…	Curated	Algorithms	`AIMech:UpwardDownwardNestedAntitheticMixture`	6 claims 1 source
Upward-downward shifted tower mixture A finite conditional Markov update that equally mixes maximum-shift tower kernels built from paired upward and downward cyclic state orders,…	Curated	Algorithms	`AIMech:UpwardDownwardShiftedTowerMixture`	6 claims 1 source
Usage-based TD(lambda) An on-policy linear state-value prediction algorithm that combines ordinary accumulating TD eligibility traces with componentwise step sizes…	Curated	Algorithms	`AIMech:UsageBasedTDLambda`	6 claims 1 source
Usage-based true online TD(lambda) An on-policy linear state-value prediction algorithm that combines componentwise inverse feature-usage step sizes with a component-scaled Du…	Curated	Algorithms	`AIMech:UsageBasedTrueOnlineTDLambda`	6 claims 1 source
Use And Interpretation Bias aka Interpretive Bias A computational bias characterized by inappropriately analyzing ambiguous stimuli scenarios and events.	AIO	Bias	`AIO:UseAndInterpretationBias`	Imported
User Interaction Bias An individual bias arising when a user imposes their own biases during interaction with data output results etc.	AIO	Bias	`AIO:UserInteractionBias`	Imported
Value-based abstraction functions for abstraction sampling aka Value-based abstraction sampling A family of graphical-model sampling abstractions that assigns a positive scalar value to each current search node and partitions nodes in v…	Curated	Mathematical Methods	`AIMech:ValueBasedAbstractionSampling`	6 claims 1 source
Vanilla sequence beam decoding aka Vanilla beam decoding A layer-based sequence beam decoder in which completed and unfinished hypotheses compete for the same k beam slots: finished hypotheses are…	Curated	Algorithms	`AIMech:VanillaSequenceBeamDecoding`	2 claims 2 sources
Vanishing gradient regularization A recurrent-network training regularization procedure that softly penalizes deviations from unit norm gain when a local recurrent Jacobian t…	Curated	Algorithms	`AIMech:VanishingGradientRegularization`	6 claims 3 sources
Variable neighborhood search A local-search metaheuristic that repeatedly perturbs an incumbent through an indexed collection of neighborhoods, locally optimizes the per…	Curated	Algorithms	`AIMech:VariableNeighborhoodSearch`	5 claims 1 source
Variational Auto Encoder aka VAE An autoencoder network that imposes a probabilistic structure on the latent space for unsupervised learning.	AIO	Network	`AIO:VariationalAutoEncoder`	Imported
Variational Expectation Maximization aka Variational EM, VEM (variational expectation maximization) A latent-variable model-fitting procedure that alternates optimization of a posterior approximation within a specified restricted family and…	Curated	Algorithms	`AIMech:VariationalExpectationMaximization`	4 claims 1 source
Variational Fair Autoencoder aka VFAE A variational autoencoder architecture for learning representations with reduced sensitive or nuisance information, combining sensitive-vari…	Curated	Architectures	`AIMech:VariationalFairAutoencoder`	1 claim 1 source
Variational information maximization IM algorithm aka IM algorithm, IM algorithm (Barber and Agakov) An alternating optimization procedure that adjusts a noisy encoder and a variational decoder to increase the Barber–Agakov lower bound on tr…	Curated	Algorithms	`AIMech:VariationalInformationMaximizationIMAlgorithm`	1 claim 1 source
Variational message passing aka VMP A variational inference algorithm that organizes conjugate-exponential coordinate updates as local messages carrying expected sufficient sta…	Curated	Algorithms	`AIMech:VariationalMessagePassing`	7 claims 1 source
Variational sparse-spectrum Gaussian-process inference aka VSSGP The Gal–Turner finite spectral regression inference procedure that factorizes spectral parameters from output coefficients, analytically opt…	Curated	Algorithms	`AIMech:VariationalSparseSpectrumGaussianProcessInference`	5 claims 3 sources
Vector Autoregression aka VAR A model that captures the linear interdependencies among multiple time series, where each variable is modeled as a linear function of its ow…	AIO	Model	`AIO:VectorAutoregression`	Imported
Vertex Attention Interaction Network aka VAIN A neural architecture for multi-agent predictive modeling that encodes each agent separately, aggregates communication vectors using learned…	Curated	Architectures	`AIMech:VertexAttentionInteractionNetwork`	6 claims 1 source
Vicinal risk minimization aka VRM A risk-minimization principle that chooses a predictor from a specified function class by minimizing expected loss under an estimated distri…	Curated	Mathematical Methods	`AIMech:VicinalRiskMinimization`	1 claim 1 source
VICReg aka Variance-invariance-covariance regularization A self-supervised joint-embedding procedure that combines a paired-view invariance loss with separate per-branch penalties for insufficient…	Curated	Algorithms	`AIMech:VICReg`	1 claim 4 sources
Virtual adversarial training aka VAT A prediction-smoothing regularization procedure that trains a model to preserve its current output distribution under approximately worst-ca…	Curated	Algorithms	`AIMech:VirtualAdversarialTraining`	1 claim 4 sources
Vocabulary Reduction aka Lexical Simplification, Lexicon Pruning… A data preparation that limits the number of unique tokens in a language model's vocabulary by merging or eliminating less frequent tokens t…	AIO	Preprocessing	`AIO:VocabularyReduction`	Imported
Voting classifier aka Hard voting, Soft voting A classifier combining base predictions through class votes or aggregated class probabilities.	Curated	Model Families	`AIMech:VotingClassifier`	1 claim 1 source
Wake-sleep algorithm aka Wake-sleep An alternating learning procedure that trains a generative network from observed data and recognition-sampled hidden states during wake, and…	Curated	Algorithms	`AIMech:WakeSleepAlgorithm`	1 claim 3 sources
WalkSAT aka WalkSAT/SKC, SKC WalkSAT A clause-focused SAT local-search algorithm, in its classical SKC formulation, that first selects an unsatisfied clause, prioritizes a varia…	Curated	Algorithms	`AIMech:WalkSAT`	1 claim 2 sources
Ward minimum-variance clustering aka Ward hierarchical clustering, Ward minimum-variance method… An agglomerative clustering algorithm for Euclidean observations that starts from singletons and repeatedly merges the pair causing the smal…	Curated	Algorithms	`AIMech:WardMinimumVarianceClustering`	6 claims 2 sources
Watkins hard-cut multistep Q-learning The original hard-cut multistep Q-learning construction that estimates action returns using maximum-value bootstraps and continuation throug…	Curated	Algorithms	`AIMech:WatkinsHardCutMultistepQLearning`	5 claims 1 source
Wavelet-domain hidden Markov model aka Wavelet hidden Markov model, Wavelet-domain HMM A statistical wavelet-coefficient model family using latent mixture states to represent coefficient distributions and Markov dependencies am…	Curated	Model Families	`AIMech:WaveletHiddenMarkovModel`	1 claim 1 source
Weighted A-star search aka Weighted A, WA A heuristic best-first search algorithm that orders open nodes by g+w h using a fixed finite weight w greater than one, where g is path cost…	Curated	Algorithms	`AIMech:WeightedAStar`	3 claims 3 sources
Weighted Layer A layer of values to be applied to other cells or neurons in a network.	AIO	Layer	`AIO:WeightedLayer`	Imported
Weighted Multiview Convex Mixture Clustering aka Weighted Multiview CMM Clustering A multiview exemplar-clustering procedure that learns shared exemplar weights and view weights through outer view-responsibility updates and…	Curated	Algorithms	`AIMech:WeightedMultiviewConvexMixtureClustering`	5 claims 1 source
Weighted Multiview Spectral Clustering aka MVSpec, Tzortzis-Likas Multiview Spectral Clustering A multiview clustering algorithm that alternates a leading-eigenspace relaxation of within-cluster variance with simplex weights for a power…	Curated	Algorithms	`AIMech:WeightedMultiviewSpectralClustering`	6 claims 1 source
Whitening mean squared error aka W-MSE, Whitening MSE A self-supervised representation-learning procedure that differentiably whitens projected image-view embeddings and minimizes the average sq…	Curated	Algorithms	`AIMech:WhiteningMSE`	1 claim 5 sources
Wiener model A real-valued, single-input single-output, discrete-time deterministic nonlinear dynamical model family formed by a causal linear time-invar…	Curated	Model Families	`AIMech:WienerModel`	4 claims 1 source
Wiener–Hammerstein model A real-valued, single-input single-output, discrete-time deterministic dynamical model family formed by a causal linear time-invariant block…	Curated	Model Families	`AIMech:WienerHammersteinModel`	4 claims 1 source
WIS-GTD(lambda) A linear off-policy state-value prediction algorithm that combines an importance-weighted accumulating eligibility trace and an auxiliary GT…	Curated	Algorithms	`AIMech:WISGTDLambda`	6 claims 1 source
WIS-TD(lambda) A linear off-policy state-value prediction algorithm that combines component step sizes from feature usage, a scaled Dutch eligibility trace…	Curated	Algorithms	`AIMech:WISTDLambda`	6 claims 1 source
WIS-TO-GTD(lambda) A linear off-policy state-value prediction adaptation of true online GTD(lambda) that derives componentwise main-weight step sizes from feat…	Curated	Algorithms	`AIMech:WISTrueOnlineGTDLambda`	6 claims 3 sources
word2vec aka W2V A machine learning task that generates distributed representations of words by training a shallow neural network model, which aims to predic…	AIO	MachineLearningTask	`AIO:word2vec`	Imported
word2vec-CBOW aka W2V-CBOW, CBOW A word2vec that predicts the current word from a window of surrounding context words, ignoring the order of context words.	AIO	MachineLearningTask	`AIO:word2vecCBOW`	Imported
word2vec-SkipGram aka W2V-SkipGram, SkipGram A word2vec that predicts surrounding context words from the current word, giving more weight to nearby context words than distant ones.	AIO	MachineLearningTask	`AIO:word2vecSkipGram`	Imported
Wrapper Layer A layer that augment the functionality of another layer.	AIO	Layer	`AIO:WrapperLayer`	Imported
Zero-self downward nested antithetic modification A finite conditional sampling construction that follows downward nested antithetic modification and replaces stages retaining avoidable self…	Curated	Algorithms	`AIMech:ZeroSelfDownwardNestedAntitheticModification`	6 claims 1 source
Zero-self flattened slice sampling A finite categorical conditional-update algorithm that flattens probability bars and relocates a qualifying blocker before the maximum-proba…	Curated	Algorithms	`AIMech:ZeroSelfFlattenedSliceSampling`	6 claims 1 source
Zero-shot Learning aka ZSL A deep neural network that predicts classes at test time from classes not observed during training.	AIO	Network	`AIO:ZeroshotLearning`	Imported
Zero-Shot Learning LLM aka Zero-Shot LLM, zero-shot learning A large language model which performs tasks or understands concepts it has not explicitly been trained on, demonstrating a high degree of ge…	AIO	Model	`AIO:ZeroShotLearningLLM`	Imported
ZeroPadding1D Layer A reshaping layer that zero-pads the input along the time axis.	AIO	Layer	`AIO:ZeroPadding1DLayer`	Imported
ZeroPadding2D Layer A reshaping layer that zero-pads the input along the height and width dimensions.	AIO	Layer	`AIO:ZeroPadding2DLayer`	Imported
ZeroPadding3D Layer A reshaping layer that zero-pads the input along the depth, height and width dimensions.	AIO	Layer	`AIO:ZeroPadding3DLayer`	Imported
Zeta merging An agglomerative graph-clustering algorithm that selects the pair with the largest sum of conditional increases in average log-diagonal reso…	Curated	Algorithms	`AIMech:ZetaMerging`	2 claims 1 source
Zhou first-passage attractor community detection aka Zhou local and global attractor communities A graph community-detection algorithm that forms local or global groups as the minimal nonempty sets closed under a first-passage-time attra…	Curated	Algorithms	`AIMech:ZhouAttractorCommunityDetection`	6 claims 1 source
Zhou random-walk distance-profile dissimilarity aka Zhou neighbor dissimilarity index A pairwise graph dissimilarity that compares the mean first-passage-time profiles of two adjacent vertices by taking the Euclidean norm of t…	Curated	Mathematical Methods	`AIMech:ZhouRandomWalkDissimilarity`	6 claims 2 sources
Zoneout A recurrent-network regularization procedure that randomly preserves selected state components at their previous values instead of applying…	Curated	Algorithms	`AIMech:Zoneout`	1 claim 1 source