SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

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Showing 361–370 of 3304 papers

TitleStatusHype
Cost-informed dimensionality reduction for structural digital twin technologies—0
HAVANA: Hierarchical stochastic neighbor embedding for Accelerated Video ANnotAtions—0
A clustering adaptive Gaussian process regression method: response patterns based real-time prediction for nonlinear solid mechanics problems—0
Multiview Canonical Correlation Analysis for Automatic Pathological Speech Detection—0
Relevance for Human Robot Collaboration—0
TopoMap++: A faster and more space efficient technique to compute projections with topological guarantees—0
Stratospheric aerosol source inversion: Noise, variability, and uncertainty quantification—0
Applications of machine learning to predict seasonal precipitation for East Africa—0
The Surprising Robustness of Partial Least Squares—0
Bridging Autoencoders and Dynamic Mode Decomposition for Reduced-order Modeling and Control of PDEs—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