SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1931–1940 of 3304 papers

TitleStatusHype
On Path Integration of Grid Cells: Group Representation and Isotropic ScalingCode1
Precise expressions for random projections: Low-rank approximation and randomized Newton—0
Isometric Autoencoders—0
Dimensionality reduction via path integration for computing mRNA distributions—0
Supervised Visualization for Data Exploration—0
Markov-Lipschitz Deep LearningCode1
Sample complexity and effective dimension for regression on manifolds—0
Analysis of Trade-offs in Fair Principal Component Analysis Based on Multi-objective OptimizationCode0
Deep Dimension Reduction for Supervised Representation LearningCode1
An Augmented Translation Technique for low Resource language pair: Sanskrit to Hindi translation—0
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All datasetsMCAEMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9—Unverified
2tSNEClassification Accuracy51.5—Unverified
3IVISClassification Accuracy46.6—Unverified
4UMAPClassification Accuracy41.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1—Unverified
2QSClassification Accuracy68—Unverified