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 1011–1020 of 3304 papers

TitleStatusHype
UNO-QA: An Unsupervised Anomaly-Aware Framework with Test-Time Clustering for OCTA Image Quality Assessment—0
Anticancer Peptides Classification using Kernel Sparse Representation ClassifierCode0
Prediction of Auto Insurance Risk Based on t-SNE Dimensionality Reduction—0
The Underlying Correlated Dynamics in Neural Training—0
Two-sample test based on Self-Organizing Maps—0
Graphon Pooling for Reducing Dimensionality of Signals and Convolutional Operators on Graphs—0
Information retrieval in single cell chromatin analysis using TF-IDF transformation methods—0
SpaceEditing: Integrating Human Knowledge into Deep Neural Networks via Interactive Latent Space Editing—0
Signal enhancement for two-dimensional cryo-EM data processingCode0
Shining light on data: Geometric data analysis through quantum dynamics—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