SOTAVerified|Agents Browse Leaderboard About

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 41–50 of 3304 papers

Title	Date	Tasks	Status	Hype	Score
ActUp: Analyzing and Consolidating tSNE and UMAP	May 12, 2023	Dimensionality Reduction	CodeCode Available	1	5
Autoencoding with a Classifier System	Oct 23, 2019	DecoderDimensionality Reduction	CodeCode Available	1	5
BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders	Mar 6, 2020	ClusteringDecoder	CodeCode Available	1	5
Bayesian Optimization of Sampling Densities in MRI	Sep 15, 2022	Bayesian OptimizationDimensionality Reduction	CodeCode Available	1	5
Adversarial Autoencoders	Nov 18, 2015	ClusteringData Visualization	CodeCode Available	1	5
BIKED: A Dataset for Computational Bicycle Design with Machine Learning Benchmarks	Mar 10, 2021	BIG-bench Machine LearningDesign Synthesis	CodeCode Available	1	5
Clustering with UMAP: Why and How Connectivity Matters	Aug 12, 2021	ClusteringDimensionality Reduction	CodeCode Available	1	5
Collection Space Navigator: An Interactive Visualization Interface for Multidimensional Datasets	May 11, 2023	Data VisualizationDimensionality Reduction	CodeCode Available	1	5
Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reduction	Jun 8, 2021	Bayesian InferenceDimensionality Reduction	CodeCode Available	1	5
ATD: Augmenting CP Tensor Decomposition by Self Supervision	Jun 15, 2021	Data AugmentationDimensionality Reduction	CodeCode Available	1	5

Show:10 25 50

← PrevPage 5 of 331Next →

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