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 2421–2430 of 3304 papers

TitleStatusHype
VoxelHop: Successive Subspace Learning for ALS Disease Classification Using Structural MRI—0
Wasserstein Auto-Encoders of Merge Trees (and Persistence Diagrams)—0
Wasserstein Dictionaries of Persistence Diagrams—0
Wasserstein Projection Pursuit of Non-Gaussian Signals—0
Watershed of Artificial Intelligence: Human Intelligence, Machine Intelligence, and Biological Intelligence—0
Wavelet Based Dictionaries for Piecewise Dimensionality Reduction of ECG Signals—0
Weakly-correlated synapses promote dimension reduction in deep neural networks—0
Web image annotation by diffusion maps manifold learning algorithm—0
Weighted Low Rank Matrix Approximation and Acceleration—0
WeightScale: Interpreting Weight Change in Neural Networks—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