Geometry and statistics-preserving manifold embedding for nonlinear dimensionality reduction-Reference-Cited by-同舟云学术

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Geometry and statistics-preserving manifold embedding for nonlinear dimensionality reduction

Published:2021-11 Issue: Volume:151 Page:155-162
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Islam Md Tauhidul,Xing Lei

Funder

National Institutes of Health

Google

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference21 articles.

1. The isomap algorithm and topological stability;Balasubramanian;Science,2002

2. Dimensionality reduction for visualizing single-cell data using UMAP;Becht;Nat. Biotechnol.,2019

3. Laplacian eigenmaps for dimensionality reduction and data representation;Belkin;Neural Comput,2003

4. Computations underlying the execution of movement: abiological perspective;Bizzi;Science,1991

5. Learning the hidden structure of speech;Elman;J. Acoust. Soc. Am.,1988

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