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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 731–740 of 3304 papers

Title	Date	Tasks	Status	Hype	Score
Beyond the Nucleus: Cytoplasmic Dominance in Follicular Thyroid Carcinoma Detection Using Single-Cell Raman Imaging Across Multiple Devices	Apr 11, 2019	DiagnosticDimensionality Reduction	CodeCode Available	0	5
MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variability	May 22, 2023	Decision MakingDimensionality Reduction	CodeCode Available	0	5
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation	Nov 19, 2023	Dimensionality ReductionRepresentation Learning	CodeCode Available	0	5
Modelling Technical and Biological Effects in scRNA-seq data with Scalable GPLVMs	Sep 14, 2022	Data IntegrationDimensionality Reduction	CodeCode Available	0	5
Adversarially-Trained Nonnegative Matrix Factorization	Apr 10, 2021	Dimensionality ReductionMatrix Completion	CodeCode Available	0	5
Demixed principal component analysis of population activity in higher cortical areas reveals independent representation of task parameters	Oct 22, 2014	Decision MakingDimensionality Reduction	CodeCode Available	0	5
Derivative-enhanced Deep Operator Network	Feb 29, 2024	Dimensionality Reduction	CodeCode Available	0	5
Co-orchestration of Multiple Instruments to Uncover Structure-Property Relationships in Combinatorial Libraries	Feb 3, 2024	Bayesian OptimizationDimensionality Reduction	CodeCode Available	0	5
Multivariate Functional Linear Discriminant Analysis for the Classification of Short Time Series with Missing Data	Feb 20, 2024	Dimensionality ReductionMissing Values	CodeCode Available	0	5
Deep Temporal Clustering: Fully unsupervised learning of time-domain features	Jan 1, 2018	ClusteringDimensionality Reduction	CodeCode Available	0	5

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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