SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2401–2410 of 3304 papers

TitleStatusHype
GAN-EM: GAN based EM learning framework—0
Robust Subspace Approximation in a Stream—0
Model-based targeted dimensionality reduction for neuronal population data—0
Manifold Coordinates with Physical MeaningCode0
RetinaMatch: Efficient Template Matching of Retina Images for Teleophthalmology—0
A Visual Interaction Framework for Dimensionality Reduction Based Data Exploration—0
Detailed Investigation of Deep Features with Sparse Representation and Dimensionality Reduction in CBIR: A Comparative Study—0
Enhanced Expressive Power and Fast Training of Neural Networks by Random ProjectionsCode0
Global Sensitivity Analysis of High Dimensional Neuroscience Models: An Example of Neurovascular Coupling—0
An interpretable multiple kernel learning approach for the discovery of integrative cancer subtypes—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