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Spatiotemporal Persistent Homology for Dynamic Metric Spaces

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Year: 2020
Type: article
Source: Discrete & Computational Geometry
DOI: 10.1007/s00454-019-00168-w
Authors: Woojin Kim, Facundo Mémoli
Institution: The Ohio State University
Language: English

Topic: Topological and Geometric Data Analysis
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences

Open Access status: green

Funder: National Science Foundation
Awards: AF: Small: Analyzing Complex Data with a Topological Lens, RI: Small: Collaborative Research: Robustness of spatial learning in flickering networks: the case of the hippocampus, Collaborative Research: The Topology of Functional Data on Random Metric Spaces, Graphs, and Graphons, TRIPODS: Topology, Geometry, and Data Analysis (TGDA@OSU):Discovering Structure, Shape, and Dynamics in Data
OpenAlex ID: W2991962490
FWCI: 4.573
Cites: 83
Cited by: 40
Related to: 10
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