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 2321–2330 of 3304 papers

TitleStatusHype
Uncertainty Quantification in Stochastic Economic Dispatch using Gaussian Process Emulation—0
Uncertainty Quantification of Darcy Flow through Porous Media using Deep Gaussian Process—0
Understanding Aesthetic Evaluation using Deep Learning—0
Understanding and Improving Multi-Sense Word Embeddings via Extended Robust Principal Component Analysis—0
Understanding Boltzmann Machine and Deep Learning via A Confident Information First Principle—0
Understanding Brain Dynamics for Color Perception using Wearable EEG headband—0
Understanding Clinical Decision-Making in Traditional East Asian Medicine through Dimensionality Reduction: An Empirical Investigation—0
Understanding Contrastive Learning via Gaussian Mixture Models—0
Understanding Deep Learning defenses Against Adversarial Examples Through Visualizations for Dynamic Risk Assessment—0
Understanding Memory Modules on Learning Simple Algorithms—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