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 271–280 of 3304 papers

TitleStatusHype
3D Shape Registration Using Spectral Graph Embedding and Probabilistic Matching—0
A novel information gain-based approach for classification and dimensionality reduction of hyperspectral images—0
A Multi-view Dimensionality Reduction Algorithm Based on Smooth Representation Model—0
A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification—0
A Class-Based Agreement Model for Generating Accurately Inflected Translations—0
A Multimodal Intermediate Fusion Network with Manifold Learning for Stress Detection—0
A Multimodal Deep Learning Approach for White Matter Shape Prediction in Diffusion MRI Tractography—0
A Deep Learning approach for parametrized and time dependent Partial Differential Equations using Dimensionality Reduction and Neural ODEs—0
A Novel Filter Approach for Band Selection and Classification of Hyperspectral Remotely Sensed Images Using Normalized Mutual Information and Support Vector Machines—0
A Multimodal Data-driven Framework for Anxiety Screening—0
Show:102550
← PrevPage 28 of 331Next →
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