A Graph‐Based Machine Learning Framework to Assign Empirical Interaction Parameters for Novel Molecules

Yao Fu, Martin Stroet, Megan L. O'Mara

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DOI: 10.1002/jcc.70508
Published: 2026-09-14
Container: Journal of Computational Chemistry
Publisher: Wiley
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1002/jcc.70508,
  title = {A Graph‐Based Machine Learning Framework to Assign Empirical Interaction Parameters for Novel Molecules},
  author = {Yao Fu and Martin Stroet and Megan L. O'Mara},
  year = {2026},
  journal = {Journal of Computational Chemistry},
  doi = {10.1002/jcc.70508},
  url = {https://doi.org/10.1002/jcc.70508}
}

RIS

TY  - JOUR
TI  - A Graph‐Based Machine Learning Framework to Assign Empirical Interaction Parameters for Novel Molecules
AU  - Yao Fu
AU  - Martin Stroet
AU  - Megan L. O'Mara
PY  - 2026
JO  - Journal of Computational Chemistry
DO  - 10.1002/jcc.70508
UR  - https://doi.org/10.1002/jcc.70508
ER  -

APA

Fu, Y., Stroet, M., & O'Mara, M. L. (2026). A Graph‐Based Machine Learning Framework to Assign Empirical Interaction Parameters for Novel Molecules. Journal of Computational Chemistry. https://doi.org/10.1002/jcc.70508

Source records

crossref · retrieved 2026-09-26T00:23:59.244Z