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 2031–2040 of 3304 papers

TitleStatusHype
Molecular Insights from Conformational Ensembles via Machine LearningCode1
Optimal Iterative Sketching with the Subsampled Randomized Hadamard Transform—0
NCVis: Noise Contrastive Approach for Scalable VisualizationCode1
Detecting Changes in Asset Co-Movement Using the Autoencoder Reconstruction Ratio—0
Optimal estimation of sparse topic models—0
ProjectionPathExplorer: Exploring Visual Patterns in Projected Decision-Making PathsCode0
Neighborhood Structure Assisted Non-negative Matrix Factorization and its Application in Unsupervised Point-wise Anomaly Detection—0
ShapeVis: High-dimensional Data Visualization at Scale—0
Unifying Deep Local and Global Features for Image SearchCode1
Supervised Discriminative Sparse PCA with Adaptive Neighbors for Dimensionality ReductionCode0
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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