Persistent de Rham-Hodge Laplacians in Eulerian representation for manifold topological learning

Recently, topological data analysis has become a trending topic in data science and engineering. However, the key technique of topological data analysis, i.e., persistent homology, is defined on point cloud data, which does not work directly for data on manifolds. Although earlier evolutionary de Rh...

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Vydané v:	AIMS mathematics Ročník 9; číslo 10; s. 27438 - 27470
Hlavní autori:	Su, Zhe, Tong, Yiying, Wei, Guo-Wei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States AIMS Press 01.01.2024
Predmet:	manifold topological analysis manifold topological learning persistent hodge laplacian protein-ligand binding 55N31 protein-ligand binding persistent Hodge Laplacian manifold topological analysis 53Z50 manifold topological learning
ISSN:	2473-6988, 2473-6988
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