SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

Showing 29262950 of 3304 papers

TitleStatusHype
Error-Correcting Neural Networks for Two-Dimensional Curvature Computation in the Level-Set MethodCode0
A Deep Learning Framework for Assessing Physical Rehabilitation ExercisesCode0
Classifying herbal medicine origins by temporal and spectral data mining of electronic noseCode0
Stochastic Mutual Information Gradient Estimation for Dimensionality Reduction NetworksCode0
A Practical Algorithm for Topic Modeling with Provable GuaranteesCode0
Network Representation Learning: Consolidation and Renewed BearingCode0
Semi-supervised Embedding Learning for High-dimensional Bayesian OptimizationCode0
Neuc-MDS: Non-Euclidean Multidimensional Scaling Through Bilinear FormsCode0
Deep Learning of Conjugate MappingsCode0
Neural Activation Semantic Models: Computational lexical semantic models of localized neural activationsCode0
Joint Embedding of GraphsCode0
Neural Codes for Image RetrievalCode0
Transformers predicting the future. Applying attention in next-frame and time series forecastingCode0
Autonomous skill discovery with Quality-Diversity and Unsupervised DescriptorsCode0
k* Distribution: Evaluating the Latent Space of Deep Neural Networks using Local Neighborhood AnalysisCode0
Approximate Bayesian Computation with Domain Expert in the LoopCode0
Kernel Feature Selection via Conditional Covariance MinimizationCode0
Evaluating Meta-Feature Selection for the Algorithm Recommendation ProblemCode0
Deep Kernel Principal Component Analysis for Multi-level Feature LearningCode0
Classes are not Clusters: Improving Label-based Evaluation of Dimensionality ReductionCode0
Neural Dynamics Discovery via Gaussian Process Recurrent Neural NetworksCode0
Layered Models can "Automatically" Regularize and Discover Low-Dimensional Structures via Feature LearningCode0
Auto-NAHL: A Neural Network Approach for Condition-Based Maintenance of Complex Industrial SystemsCode0
Semi-Supervised Graph Learning Meets Dimensionality ReductionCode0
Pseudocell Tracer—A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombinationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified