SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 151–160 of 3304 papers

TitleStatusHype
Modern Dimension ReductionCode1
DefakeHop: A Light-Weight High-Performance Deepfake DetectorCode1
BIKED: A Dataset for Computational Bicycle Design with Machine Learning BenchmarksCode1
Explaining dimensionality reduction results using Shapley valuesCode1
Minimum-Distortion EmbeddingCode1
Unsupervised Ground Metric Learning using Wasserstein Singular VectorsCode1
OmiEmbed: a unified multi-task deep learning framework for multi-omics dataCode1
Reduced operator inference for nonlinear partial differential equationsCode1
FDApy: a Python package for functional dataCode1
Deep Convolutional Autoencoders for reconstructing magnetic resonance images of the healthy brainCode1
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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