Addressing hypersensitivity in density functional theory for reliable machine learning.

Arnstein L, Wetherell J, Lawrence R, Hasnip PJ, Hodgson MJP

Open source

DOI
10.1038/s41524-026-02191-x
Published
2026
Container
npj computational materials
Publisher
arXiv
Open access
yes

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BibTeX

@article{allodium:10.1038/s41524-026-02191-x,
  title = {Addressing hypersensitivity in density functional theory for reliable machine learning.},
  author = {Arnstein L and Wetherell J and Lawrence R and Hasnip PJ and Hodgson MJP},
  year = {2026},
  journal = {npj computational materials},
  doi = {10.1038/s41524-026-02191-x},
  url = {https://doi.org/10.1038/s41524-026-02191-x}
}

RIS

TY  - JOUR
TI  - Addressing hypersensitivity in density functional theory for reliable machine learning.
AU  - Arnstein L
AU  - Wetherell J
AU  - Lawrence R
AU  - Hasnip PJ
AU  - Hodgson MJP
PY  - 2026
JO  - npj computational materials
DO  - 10.1038/s41524-026-02191-x
UR  - https://doi.org/10.1038/s41524-026-02191-x
ER  -

APA

L, A., J, W., R, L., PJ, H., & MJP, H. (2026). Addressing hypersensitivity in density functional theory for reliable machine learning.. npj computational materials. https://doi.org/10.1038/s41524-026-02191-x

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