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 1861–1870 of 3304 papers

TitleStatusHype
Improving the generalization of network based relative pose regression: dimension reduction as a regularizer—0
Geometry-Aware Hamiltonian Variational Auto-Encoder—0
Tensor Train Random Projection—0
Integrating LEO Satellites and Multi-UAV Reinforcement Learning for Hybrid FSO/RF Non-Terrestrial Networks—0
Auto-Encoding Variational Bayes for Inferring Topics and VisualizationCode0
Statistical guarantees for generative models without domination—0
Product Manifold LearningCode0
Sufficient dimension reduction for classification using principal optimal transport directionCode0
Prediction of daily maximum ozone levels using Lasso sparse modeling method—0
Interactive Latent Interpolation on MNIST DatasetCode0
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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