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 421–430 of 3304 papers

TitleStatusHype
Single-Sequence-Based Protein Secondary Structure Prediction using One-Hot and Chemical Encodings of Amino Acids—0
Automatic Prediction of the Performance of Every Parser—0
Autoencoded Image Compression for Secure and Fast TransmissionCode0
Adversarial Robustness of VAEs across Intersectional SubgroupsCode0
Credit Risk Assessment Model for UAE Commercial Banks: A Machine Learning Approach—0
Message-Relevant Dimension Reduction of Neural Populations—0
Statistical Advantages of Oblique Randomized Decision Trees and Forests—0
Latent Diffusion Model for Generating Ensembles of Climate Simulations—0
Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Tasks—0
Fully invertible hyperbolic neural networks for segmenting large-scale surface and sub-surface data—0
Show:102550
← PrevPage 43 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