SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 451–460 of 3304 papers

TitleStatusHype
Autoencoding topology—0
A Multi-Fidelity Methodology for Reduced Order Models with High-Dimensional Inputs—0
Autoencoding with a Learning Classifier System: Initial Results—0
Bayesian model and dimension reduction for uncertainty propagation: applications in random media—0
Automated Anomaly Detection on European XFEL Klystrons—0
Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis—0
Automated Disease Normalization with Low Rank Approximations—0
Automatic Collection Creation and Recommendation—0
A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification—0
Approximated and User Steerable tSNE for Progressive Visual Analytics—0
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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