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 1581–1590 of 3304 papers

TitleStatusHype
FAST-PCA: A Fast and Exact Algorithm for Distributed Principal Component Analysis—0
Convolutional Neural Networks Demystified: A Matched Filtering Perspective Based Tutorial—0
Uniform Manifold Approximation and Projection (UMAP) and its Variants: Tutorial and Survey—0
Multi-Criteria Radio Spectrum Sharing With Subspace-Based Pareto Tracing—0
Joint Characterization of Spatiotemporal Data Manifolds—0
Transformers predicting the future. Applying attention in next-frame and time series forecastingCode0
M-ar-K-Fast Independent Component AnalysisCode0
Disease-oriented image embedding with pseudo-scanner standardization for content-based image retrieval on 3D brain MRI—0
Dimensionality Reduction and State Space Systems: Forecasting the US Treasury Yields Using Frequentist and Bayesian VARs—0
Predicting Molecular Phenotypes with Single Cell RNA Sequencing Data: an Assessment of Unsupervised Machine Learning Models—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