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 1911–1920 of 3304 papers

TitleStatusHype
Generative Modeling for Atmospheric Convection—0
Generative Models for Anomaly Detection and Design-Space Dimensionality Reduction in Shape Optimization—0
Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting—0
GENHOP: An Image Generation Method Based on Successive Subspace Learning—0
Genomics Data Analysis via Spectral Shape and Topology—0
GenURL: A General Framework for Unsupervised Representation Learning—0
Geodesic Sinkhorn for Fast and Accurate Optimal Transport on Manifolds—0
Geometric Data-Driven Dimensionality Reduction in MPC with Guarantees—0
Survey: Geometric Foundations of Data Reduction—0
Geometric Machine Learning on EEG Signals—0
Show:102550
← PrevPage 192 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