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 1411–1420 of 3304 papers

TitleStatusHype
Fréchet Cumulative Covariance Net for Deep Nonlinear Sufficient Dimension Reduction with Random Objects—0
FRE: A Fast Method For Anomaly Detection And Segmentation—0
FRANS: Automatic Feature Extraction for Time Series Forecasting—0
Generative Modeling: A Review—0
Generative Modeling for Atmospheric Convection—0
Generative Models for Anomaly Detection and Design-Space Dimensionality Reduction in Shape Optimization—0
Fractal Descriptors of Texture Images Based on the Triangular Prism Dimension—0
GENHOP: An Image Generation Method Based on Successive Subspace Learning—0
ANTLER: Bayesian Nonlinear Tensor Learning and Modeler for Unstructured, Varying-Size Point Cloud Data—0
A Correspondence Analysis Framework for Author-Conference Recommendations—0
Show:102550
← PrevPage 142 of 331Next →
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