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 1211–1220 of 3304 papers

TitleStatusHype
Bridging Fairness and Environmental Sustainability in Natural Language Processing—0
Dimension Reduction for Efficient Data-Enabled Predictive Control—0
Geodesic Sinkhorn for Fast and Accurate Optimal Transport on Manifolds—0
Genomics Data Analysis via Spectral Shape and Topology—0
A new filter for dimensionality reduction and classification of hyperspectral images using GLCM features and mutual information—0
A Faster Approach to Spiking Deep Convolutional Neural Networks—0
Gravitational Dimensionality Reduction Using Newtonian Gravity and Einstein's General RelativityCode0
Hybridization of filter and wrapper approaches for the dimensionality reduction and classification of hyperspectral images—0
Adaptive physics-informed neural operator for coarse-grained non-equilibrium flows—0
Hyperspectral Images Classification and Dimensionality Reduction using spectral interaction and SVM classifier—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