Article Extraction of physicochemical laws by symbolic regression using a Bayesian information criterion

Naoki Yamane (Tsukuba University) ; Kan Hatakeyama-Sato (東京工業大学) ; Yuma Iwasaki SAMURAI ORCID (Center for Basic Research on Materials/Data-driven Materials Research Field/Data-driven Materials Design Group, National Institute for Materials Science) ; Yasuhiko Igarashi (Tsukuba University)

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Naoki Yamane, Kan Hatakeyama-Sato, Yuma Iwasaki, Yasuhiko Igarashi. Extraction of physicochemical laws by symbolic regression using a Bayesian information criterion. Science and Technology of Advanced Materials: Methods. 2024, 4 (1), . https://doi.org/10.1080/27660400.2024.2420658
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(abstract)

ベイズ情報基準を活用した独自のSymbolic regressionアルゴリズム

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Keyword: Machine learning

Date published: 2024-12-31

Publisher: Taylor & Francis

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  • Science and Technology of Advanced Materials: Methods (ISSN: 27660400) vol. 4 issue. 1

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Manuscript type: Publisher's version (Version of record)

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First published URL: https://doi.org/10.1080/27660400.2024.2420658

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Updated at: 2024-11-14 16:30:30 +0900

Published on MDR: 2024-11-14 16:30:30 +0900

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