SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

Showing 251275 of 3304 papers

TitleStatusHype
A Deep Learning Framework for Assessing Physical Rehabilitation ExercisesCode0
Analyzing scRNA-seq data by CCP-assisted UMAP and t-SNECode0
A distribution-dependent Mumford-Shah model for unsupervised hyperspectral image segmentationCode0
Effective Dimensionality Reduction for Word EmbeddingsCode0
Dimension reduction methods, persistent homology and machine learning for EEG signal analysis of Interictal Epileptic DischargesCode0
Reducing the dimensionality of data using tempered distributionsCode0
Dimension Reduction and MARSCode0
Dimension Reduction for Data with Heterogeneous MissingnessCode0
A Grid-based Method for Removing Overlaps of Dimensionality Reduction Scatterplot LayoutsCode0
Dimensionality reduction, regularization, and generalization in overparameterized regressionsCode0
Analysis of Trade-offs in Fair Principal Component Analysis Based on Multi-objective OptimizationCode0
Dimensionality Reduction Meets Message Passing for Graph Node EmbeddingsCode0
Dimensionality reduction of neuronal degeneracy reveals two interfering physiological mechanismsCode0
Dimensionality Reduction using Similarity-induced EmbeddingsCode0
Dimensionality Reduction for Binary Data through the Projection of Natural ParametersCode0
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation ApproachCode0
Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image SegmentationCode0
DiffRed: Dimensionality Reduction guided by stable rankCode0
A more globally accurate dimensionality reduction method using tripletsCode0
Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon ForecastingCode0
Weight Matrix Dimensionality Reduction in Deep Learning via Kronecker Multi-layer ArchitecturesCode0
Dimension-reduced Optimization of Multi-zone Thermostatically Controlled LoadsCode0
Efficient Manifold and Subspace Approximations with SphereletsCode0
Detecting Adversarial Examples through Nonlinear Dimensionality ReductionCode0
A Mixture of Matrix Variate Bilinear Factor AnalyzersCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified