SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1531–1540 of 3304 papers

TitleStatusHype
Computer-aided Interpretable Features for Leaf Image ClassificationCode0
HUMAP: Hierarchical Uniform Manifold Approximation and ProjectionCode1
Discovering Interpretable Machine Learning Models in Parallel Coordinates—0
Quantum diffusion map for nonlinear dimensionality reduction—0
Improving Metric Dimensionality Reduction with Distributed TopologyCode1
Distributionally Robust Optimization with Markovian DataCode0
Quantifying the Conceptual Error in Dimensionality Reduction—0
Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models—0
Unsupervised Behaviour Discovery with Quality-Diversity OptimisationCode1
Large-scale optimal transport map estimation using projection pursuitCode1
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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