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 1311–1320 of 3304 papers

TitleStatusHype
FRE: A Fast Method For Anomaly Detection And Segmentation—0
FFTLasso: Large-Scale LASSO in the Fourier Domain—0
Computational Graph Completion—0
Free Lunch for Gait Recognition: A Novel Relation Descriptor—0
From Pretext to Purpose: Batch-Adaptive Self-Supervised Learning—0
Fully invertible hyperbolic neural networks for segmenting large-scale surface and sub-surface data—0
Finding Pegasus: Enhancing Unsupervised Anomaly Detection in High-Dimensional Data using a Manifold-Based Approach—0
Finding Real-World Orbital Motion Laws from Data—0
Finding Rule-Interpretable Non-Negative Data Representation—0
Game Theory Meets Statistical Mechanics in Deep Learning Design—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