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 321–330 of 3304 papers

TitleStatusHype
Principal Orthogonal Latent Components Analysis (POLCA Net)Code0
Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility—0
Learning Image Derived PDE-Phenotypes from fMRI Data—0
Precision Cancer Classification and Biomarker Identification from mRNA Gene Expression via Dimensionality Reduction and Explainable AI—0
Contrastive Learning to Fine-Tune Feature Extraction Models for the Visual Cortex—0
ESPACE: Dimensionality Reduction of Activations for Model Compression—0
Random-projection ensemble dimension reductionCode0
Efficient Large-Scale Urban Parking Prediction: Graph Coarsening Based on Real-Time Parking Service Capability—0
Enhanced MRI brain tumor detection and classification via topological data analysis and low-rank tensor decompositionCode1
On metric choice in dimension reduction for Fréchet regression—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