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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Veröffentlicht in:	AIMS mathematics Jg. 9; H. 10; S. 27438 - 27470
Hauptverfasser:	Su, Zhe, Tong, Yiying, Wei, Guo-Wei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States AIMS Press 01.01.2024
Schlagworte:	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
Online-Zugang:	Volltext
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