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 1641–1650 of 3304 papers

TitleStatusHype
Abstraction and Symbolic Execution of Deep Neural Networks with Bayesian Approximation of Hidden Features—0
SCALE SPACE FLOW WITH AUTOREGRESSIVE PRIORS—0
Hard-label Manifolds: Unexpected Advantages of Query Efficiency for Finding On-manifold Adversarial Examples—0
Lazy FSCA for Unsupervised Variable SelectionCode0
Minimum-Distortion EmbeddingCode1
FedPower: Privacy-Preserving Distributed Eigenspace Estimation—0
The Mathematics Behind Spectral Clustering And The Equivalence To PCA—0
Unsupervised dynamic modeling of medical image transformationCode0
Validating Clustering Frameworks for Electric Load Demand ProfilesCode0
Detection of Alzheimer's Disease Using Graph-Regularized Convolutional Neural Network Based on Structural Similarity Learning of Brain Magnetic Resonance Images—0
Show:102550
← PrevPage 165 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