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 601–610 of 3304 papers

TitleStatusHype
Self-Adaptive Quantum Kernel Principal Components Analysis for Compact Readout of Chemiresistive Sensor Arrays—0
On latent dynamics learning in nonlinear reduced order modeling—0
PAGE: Parametric Generative Explainer for Graph Neural NetworkCode0
ADRS-CNet: An adaptive dimensionality reduction selection and classification network for DNA storage clustering algorithms—0
Robust spectral clustering with rank statistics—0
OPDR: Order-Preserving Dimension Reduction for Semantic Embedding of Multimodal Scientific Data—0
Quantum-inspired Interpretable Deep Learning Architecture for Text Sentiment AnalysisCode0
"Normalized Stress" is Not Normalized: How to Interpret Stress CorrectlyCode0
Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling—0
Feature-Preserving Rate-Distortion Optimization in Image Coding for Machines—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