SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 791–800 of 3304 papers

TitleStatusHype
Gaussian Image Anomaly Detection with Greedy Eigencomponent Selection—0
Deep Learning Architecture for Motor Imaged Words—0
Machine Learning, Deep Learning and Data Preprocessing Techniques for Detection, Prediction, and Monitoring of Stress and Stress-related Mental Disorders: A Scoping Review—0
ScatterUQ: Interactive Uncertainty Visualizations for Multiclass Deep Learning ProblemsCode0
Generative Models for Anomaly Detection and Design-Space Dimensionality Reduction in Shape Optimization—0
Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image SegmentationCode0
Visualization of Extremely Sparse Contingency Table by Taxicab Correspondence Analysis: A Case Study of Textual Data—0
Flashlight Search Medial Axis: A Pixel-Free Pore-Network Extraction Algorithm—0
Fast and Accurate Reduced-Order Modeling of a MOOSE-based Additive Manufacturing Model with Operator Learning—0
Regular Variation in Hilbert Spaces and Principal Component Analysis for Functional Extremes—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