SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 29412950 of 3304 papers

TitleStatusHype
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