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
ResFeats: Residual Network Based Features for Image Classification—0
ReStoCNet: Residual Stochastic Binary Convolutional Spiking Neural Network for Memory-Efficient Neuromorphic Computing—0
Restricted Boltzmann Machine and Deep Belief Network: Tutorial and Survey—0
Restricted Isometry Property of Gaussian Random Projection for Finite Set of Subspaces—0
Restricted Isometry Property under High Correlations—0
Rethinking Dimensionality Reduction in Grid-based 3D Object Detection—0
Rethinking the editing of generative adversarial networks: a method to estimate editing vectors based on dimension reduction—0
RetinaMatch: Efficient Template Matching of Retina Images for Teleophthalmology—0
Revealing computational mechanisms of retinal prediction via model reduction—0
Reverse Markov Learning: Multi-Step Generative Models for Complex Distributions—0
Show:102550
← PrevPage 194 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