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 2041–2050 of 3304 papers

TitleStatusHype
A Correspondence Analysis Framework for Author-Conference Recommendations—0
A kernel Principal Component Analysis (kPCA) digest with a new backward mapping (pre-image reconstruction) strategy—0
Review of Single-cell RNA-seq Data Clustering for Cell Type Identification and Characterization—0
Upper bounds for Model-Free Row-Sparse Principal Component Analysis—0
Estimating Model Uncertainty of Neural Network in Sparse Information Form—0
MODiR: Multi-Objective Dimensionality Reduction for Joint Data Visualisation—0
Measuring group-separability in geometrical space for evaluation of pattern recognition and embedding algorithms—0
Interpreting LSTM Prediction on Solar Flare Eruption with Time-series ClusteringCode0
Interpretable Embeddings From Molecular Simulations Using Gaussian Mixture Variational AutoencodersCode0
Deep learning to discover and predict dynamics on an inertial manifoldCode0
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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