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 3041–3050 of 3304 papers

TitleStatusHype
Deep Features for training Support Vector Machine—0
Deep Gaussian Mixture Models—0
Deep Generative Models Strike Back! Improving Understanding and Evaluation in Light of Unmet Expectations for OoD Data—0
Deep-gKnock: nonlinear group-feature selection with deep neural network—0
Deep learning and differential equations for modeling changes in individual-level latent dynamics between observation periods—0
Estimation of a function of low local dimensionality by deep neural networks—0
Deep learning approach based on dimensionality reduction for designing electromagnetic nanostructures—0
Deep Learning Architecture for Motor Imaged Words—0
Deep-learning based measurement of planetary radial velocities in the presence of stellar variability—0
Deep Learning for Causal Inference—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