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 2621–2630 of 3304 papers

TitleStatusHype
Grading and Anomaly Detection for Automated Retinal Image Analysis using Deep Learning—0
A Multi-Fidelity Methodology for Reduced Order Models with High-Dimensional Inputs—0
A Multimodal Data-driven Framework for Anxiety Screening—0
A Multimodal Deep Learning Approach for White Matter Shape Prediction in Diffusion MRI Tractography—0
A Multimodal Intermediate Fusion Network with Manifold Learning for Stress Detection—0
A Multi-view Dimensionality Reduction Algorithm Based on Smooth Representation Model—0
A Music Classification Model based on Metric Learning and Feature Extraction from MP3 Audio Files—0
An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification—0
An adaptive block based integrated LDP,GLCM,and Morphological features for Face Recognition—0
ELBD: Efficient score algorithm for feature selection on latent variables of VAE—0
Show:102550
← PrevPage 263 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