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 2411–2420 of 3304 papers

TitleStatusHype
Visualising Multiplayer Game Spaces—0
Visualization of Extremely Sparse Contingency Table by Taxicab Correspondence Analysis: A Case Study of Textual Data—0
Visualizing and Exploring Dynamic High-Dimensional Datasets with LION-tSNE—0
Visualizing Data using t-SNE—0
Uncovering Temporal Patterns in Visualizations of High-Dimensional Data—0
Exploring the Geometry and Topology of Neural Network Loss Landscapes—0
Visualizing the Finer Cluster Structure of Large-Scale and High-Dimensional Data—0
Data-Efficient Machine Learning Potentials via Difference Vectors Based on Local Atomic Environments—0
Visual response properties of MSTd emerge from a sparse population code—0
VizCV: AI-assisted visualization of researchers' publications tracks—0
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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