SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 651–660 of 3304 papers

TitleStatusHype
Compression-aware Projection with Greedy Dimension Reduction for Convolutional Neural Network Activations—0
Compression supports low-dimensional representations of behavior across neural circuits—0
Compressive Feature Learning—0
Compressive Sensing Approaches for Sparse Distribution Estimation Under Local Privacy—0
Cross-Sectional Dynamics Under Network Structure: Theory and Macroeconomic Applications—0
Computational Graph Completion—0
Computational Techniques in Multispectral Image Processing: Application to the Syriac Galen Palimpsest—0
Computation of the Maximum Likelihood estimator in low-rank Factor Analysis—0
Computer-Aided Automated Detection of Gene-Controlled Social Actions of Drosophila—0
Clustering based on Mixtures of Sparse Gaussian Processes—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