SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 941950 of 3304 papers

TitleStatusHype
Improving information retrieval through correspondence analysis instead of latent semantic analysis0
A primer on correlation-based dimension reduction methods for multi-omics analysisCode0
Incentives and co-evolution: Steering linear dynamical systems with noncooperative agents0
Entropic Wasserstein Component AnalysisCode0
Differential Privacy Meets Neural Network Pruning0
Rethinking the editing of generative adversarial networks: a method to estimate editing vectors based on dimension reduction0
Sufficient dimension reduction for feature matrices0
A topological classifier to characterize brain states: When shape matters more than variance0
A Hybrid Architecture for Out of Domain Intent Detection and Intent DiscoveryCode1
Super-Resolution Neural OperatorCode0
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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