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 2851–2860 of 3304 papers

TitleStatusHype
Disentangling Topic Models: A Cross-cultural Analysis of Personal Values through Words—0
A Category Space Approach to Supervised Dimensionality Reduction—0
Bayesian latent structure discovery from multi-neuron recordingsCode0
Representation Learning with Deconvolution for Multivariate Time Series Classification and VisualizationCode0
A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data—0
UTD-CRSS Systems for 2016 NIST Speaker Recognition Evaluation—0
Variational Koopman models: slow collective variables and molecular kinetics from short off-equilibrium simulations—0
Nonlinear Structural Vector Autoregressive Models for Inferring Effective Brain Network Connectivity—0
Structured adaptive and random spinners for fast machine learning computations—0
Improving Covariance-Regularized Discriminant Analysis for EHR-based Predictive Analytics of Diseases—0
Show:102550
← PrevPage 286 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