SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 231–240 of 3304 papers

TitleStatusHype
Generative Modeling: A Review—0
Bi-Sparse Unsupervised Feature SelectionCode0
Integrating Random Effects in Variational Autoencoders for Dimensionality Reduction of Correlated Data—0
Fast Multi-Group Gaussian Process Factor Models—0
A Unifying Family of Data-Adaptive Partitioning Algorithms—0
Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics with Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis—0
Dimension Reduction with Locally Adjusted GraphsCode4
Computing Gram Matrix for SMILES Strings using RDKFingerprint and Sinkhorn-Knopp Algorithm—0
ICA-based Resting-State Networks Obtained on Large Autism fMRI Dataset ABIDECode0
Progressive Monitoring of Generative Model Training Evolution—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