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Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 3021–3030 of 3304 papers

Title	Date	Tasks	Status	Hype
ShaRP: Shape-Regularized Multidimensional Projections	Jun 1, 2023	Dimensionality Reduction	CodeCode Available	0
Automatic Differentiation in PyTorch	Oct 28, 2017	ClusteringCPU	CodeCode Available	0
Image Reconstruction via Deep Image Prior Subspaces	Feb 20, 2023	Dimensionality ReductionImage Reconstruction	CodeCode Available	0
Chainer: a Next-Generation Open Source Framework for Deep Learning	Jan 1, 2015	ClusteringDeep Learning	CodeCode Available	0
Deep Feature Selection using a Teacher-Student Network	Mar 17, 2019	ClusteringDimensionality Reduction	CodeCode Available	0
Learning Active Subspaces and Discovering Important Features with Gaussian Radial Basis Functions Neural Networks	Jul 11, 2023	Decision MakingDimensionality Reduction	CodeCode Available	0
Using Dimensionality Reduction to Optimize t-SNE	Dec 2, 2019	ClusteringDimensionality Reduction	CodeCode Available	0
A Flag Decomposition for Hierarchical Datasets	Feb 11, 2025	ClusteringDenoising	CodeCode Available	0
Center Smoothing: Certified Robustness for Networks with Structured Outputs	Feb 19, 2021	Adversarial RobustnessDimensionality Reduction	CodeCode Available	0
Subsurface Characterization using Ensemble-based Approaches with Deep Generative Models	Oct 2, 2023	Dimensionality ReductionGenerative Adversarial Network	CodeCode Available	0

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All datasets MCA EMNIST

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	UDRN	Classification Accuracy	90.9	—	Unverified
2	tSNE	Classification Accuracy	51.5	—	Unverified
3	IVIS	Classification Accuracy	46.6	—	Unverified
4	UMAP	Classification Accuracy	41.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UDRN	Classification Accuracy	71.1	—	Unverified
2	QS	Classification Accuracy	68	—	Unverified