SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1461–1470 of 3304 papers

TitleStatusHype
Graph Learning via Spectral Densification—0
Graph Neural Network Acceleration via Matrix Dimension Reduction—0
Foundations of Coupled Nonlinear Dimensionality Reduction—0
Graphon Pooling in Graph Neural Networks—0
Graph Regularized Autoencoder and its Application in Unsupervised Anomaly Detection—0
Graph Regularized NMF with L20-norm for Unsupervised Feature Learning—0
Foundations of a Knee Joint Digital Twin from qMRI Biomarkers for Osteoarthritis and Knee Replacement—0
Graph Signal Representation with Wasserstein Barycenters—0
Graph Transformer-Based Flood Susceptibility Mapping: Application to the French Riviera and Railway Infrastructure Under Climate Change—0
Anti-drift in electronic nose via dimensionality reduction: a discriminative subspace projection approach—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