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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/0CBDC945-F21A-4865-8B9D-21638F9F146A | ||
| Year | 2023 | ||
| Type of Item | Review | ||
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| Bibliographic Citation | D. Leykam and D. G. Angelakis, “Topological data analysis and machine learning,” Adv. Phys.: X, vol. 8, no. 1, Dec. 2023, doi: 10.1080/23746149.2023.2202331. https://doi.org/10.1080/23746149.2023.2202331 | ||
| Appears in Collections |
Topological data analysis refers to approaches for systematically and reliably computing abstract ‘shapes’ of complex data sets. There are various applications of topological data analysis in life and data sciences, with growing interest among physicists. We present a concise review of applications of topological data analysis to physics and machine learning problems in physics including the unsupervised detection of phase transitions. We finish with a preview of anticipated directions for future research.
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