SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 221230 of 3304 papers

TitleStatusHype
Targeted Visualization of the Backbone of Encoder LLMsCode1
Tensor Canonical Correlation Analysis for Multi-view Dimension ReductionCode1
Deep Learning for Reduced Order Modelling and Efficient Temporal Evolution of Fluid SimulationsCode1
Deep Learning for Functional Data Analysis with Adaptive Basis LayersCode1
Deep Learning of Individual AestheticsCode1
Deep reconstruction of strange attractors from time seriesCode1
ParaDime: A Framework for Parametric Dimensionality ReductionCode1
Trajectories, bifurcations and pseudotime in large clinical datasets: applications to myocardial infarction and diabetes dataCode1
A distribution-dependent Mumford-Shah model for unsupervised hyperspectral image segmentationCode0
DiffRed: Dimensionality Reduction guided by stable rankCode0
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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