SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 31913200 of 3304 papers

TitleStatusHype
Tuning-Free Structured Sparse PCA via Deep Unfolding NetworksCode0
SOM-VAE: Interpretable Discrete Representation Learning on Time SeriesCode0
On the Whitney near extension problem, BMO, alignment of data, best approximation in algebraic geometry, manifold learning and their beautiful connections: A modern treatmentCode0
A Systematic Performance Analysis of Deep Perceptual Loss Networks: Breaking Transfer Learning ConventionsCode0
Decomposing feature-level variation with Covariate Gaussian Process Latent Variable ModelsCode0
Adversarial Robustness of VAEs across Intersectional SubgroupsCode0
Covariance-free Partial Least Squares: An Incremental Dimensionality Reduction MethodCode0
Supervision and Source Domain Impact on Representation Learning: A Histopathology Case StudyCode0
ADAGIO: Fast Data-aware Near-Isometric Linear EmbeddingsCode0
Representation Learning with Deconvolution for Multivariate Time Series Classification and VisualizationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified