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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 1901–1910 of 3304 papers

Title	Date	Tasks	Status	Hype
Generative Modeling for Atmospheric Convection	Jul 3, 2020	ClusteringDimensionality Reduction	—Unverified	0
Deep Neural Networks for Nonlinear Model Order Reduction of Unsteady Flows	Jul 2, 2020	Dimensionality Reduction	—Unverified	0
A New Basis for Sparse Principal Component Analysis	Jul 1, 2020	ClusteringDimensionality Reduction	CodeCode Available	1
Subspace approximation with outliers	Jun 30, 2020	Dimensionality Reduction	—Unverified	0
Deep neural networks for the evaluation and design of photonic devices	Jun 30, 2020	Dimensionality Reduction	—Unverified	0
VAE-KRnet and its applications to variational Bayes	Jun 29, 2020	Density EstimationDimensionality Reduction	—Unverified	0
Local Neighbor Propagation Embedding	Jun 29, 2020	Dimensionality Reduction	—Unverified	0
Physics-aware registration based auto-encoder for convection dominated PDEs	Jun 28, 2020	Dimensionality Reduction	CodeCode Available	1
Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation Vectors	Jun 27, 2020	ClusteringDimensionality Reduction	CodeCode Available	1
The Signature Kernel is the solution of a Goursat PDE	Jun 26, 2020	Dimensionality ReductionGPU	CodeCode Available	1

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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