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 571–580 of 3304 papers

TitleStatusHype
Policy Optimization for PDE Control with a Warm Start—0
Derivative-enhanced Deep Operator NetworkCode0
Degradation Modeling and Prognostic Analysis Under Unknown Failure ModesCode0
Physics-Informed Machine Learning for Seismic Response Prediction OF Nonlinear Steel Moment Resisting Frame Structures—0
A Multi-Fidelity Methodology for Reduced Order Models with High-Dimensional Inputs—0
Quick unsupervised hyperspectral dimensionality reduction for earth observation: a comparison—0
Feature Selection Based on Orthogonal Constraints and Polygon Area—0
Inference for Regression with Variables Generated by AI or Machine Learning—0
Non-Contact Acquisition of PPG Signal using Chest Movement-Modulated Radio Signals—0
A Two-Stage Dual-Path Framework for Text Tampering Detection and Recognition—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