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 2091–2100 of 3304 papers

TitleStatusHype
Sparse Representation of 3D Images for Piecewise Dimensionality Reduction with High Quality Reconstruction—0
Sparse Representation of Multivariate Extremes with Applications to Anomaly Ranking—0
Sparse Subspace Denoising for Image Manifolds—0
Sparse Variational Bayesian Approximations for Nonlinear Inverse Problems: applications in nonlinear elastography—0
Sparsifying dimensionality reduction of PDE solution data with Bregman learning—0
Sparsistent filtering of comovement networks from high-dimensional data—0
Sparsity in Multivariate Extremes with Applications to Anomaly Detection—0
Spatial Context based Angular Information Preserving Projection for Hyperspectral Image Classification—0
Spatial noise-aware temperature retrieval from infrared sounder data—0
Spatio-Temporal Crop Aggregation for Video Representation Learning—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