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Atomistic simulation assisted error-inclusive Bayesian machine learning for probabilistically unraveling the mechanical properties of solidified metals

Crossref DOI link: https://doi.org/10.1038/s41524-024-01200-1

Published Online: 2024-01-24

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Mahata, A. https://orcid.org/0000-0002-8723-9414
Mukhopadhyay, T. https://orcid.org/0000-0002-0778-6515
Chakraborty, S. https://orcid.org/0000-0003-2383-2603
Asle Zaeem, M. https://orcid.org/0000-0002-5164-6122
Funding

Funding for this research was provided by:

National Science Foundation (2031800)
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Text and Data Mining valid from 2024-01-24

Version of Record valid from 2024-01-24
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Article History

Received: 10 August 2023

Accepted: 3 January 2024

First Online: 24 January 2024

Competing interests

: The authors declare no competing interests.

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