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 1691–1700 of 3304 papers

TitleStatusHype
Empirical Analysis of Anomaly Detection on Hyperspectral Imaging Using Dimension Reduction Methods—0
Empirical comparison between autoencoders and traditional dimensionality reduction methods—0
Empirical Evaluation of Kernel PCA Approximation Methods in Classification Tasks—0
Empowering Digital Agriculture: A Privacy-Preserving Framework for Data Sharing and Collaborative Research—0
Empowering individual trait prediction using interactions—0
Emulating the dynamics of complex systems using autoregressive models on manifolds (mNARX)—0
Emulators for stellar profiles in binary population modeling—0
End-to-end translation of human neural activity to speech with a dual-dual generative adversarial network—0
Precoder Design for Correlated Data Aggregation via Over-the-Air Computation in Sensor Networks—0
Enhanced CNN with Global Features for Fault Diagnosis of Complex Chemical 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