SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1281–1290 of 3304 papers

TitleStatusHype
A novel approach for Fair Principal Component Analysis based on eigendecompositionCode0
GANs and Closures: Micro-Macro Consistency in Multiscale Modeling—0
MetaRF: Differentiable Random Forest for Reaction Yield Prediction with a Few Trails—0
Convergent autoencoder approximation of low bending and low distortion manifold embeddingsCode0
A Graphical Model for Fusing Diverse Microbiome DataCode0
Machine learning algorithms for three-dimensional mean-curvature computation in the level-set methodCode0
Collaborative causal inference on distributed data—0
Training-Time Attacks against k-Nearest Neighbors—0
On a Mechanism Framework of Autoencoders—0
May the force be with you—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