A kernel for multi-parameter persistent homology
Topological data analysis and its main method, persistent homology, provide a toolkit for computing topological information of high-dimensional and noisy data sets. Kernels for one-parameter persistent homology have been established to connect persistent homology with machine learning techniques wit...
Main Authors: | René Corbet, Ulderico Fugacci, Michael Kerber, Claudia Landi, Bei Wang |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2019-12-01
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Series: | Computers & Graphics: X |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2590148619300056 |
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