SOTAVerified

Dimensionality Reduction

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

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 831–840 of 3304 papers

TitleStatusHype
Delamination prediction in composite panels using unsupervised-feature learning methods with wavelet-enhanced guided wave representations—0
DEMEA: Deep Mesh Autoencoders for Non-Rigidly Deforming Objects—0
Demixed Principal Component Analysis—0
A Survey on Archetypal Analysis—0
Demonstrating Superresolution in Radar Range Estimation Using a Denoising Autoencoder—0
Demystifying Embedding Spaces using Large Language Models—0
Classification of EEG Signals using Genetic Programming for Feature Construction—0
Denoising VAE as an Explainable Feature Reduction and Diagnostic Pipeline for Autism Based on Resting state fMRI—0
Density-based Isometric Mapping—0
An Improved CNN-based Neural Network Model for Fruit Sugar Level Detection—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