Synergy of semiempirical models and machine learning in computational chemistry

@article{Fedik2023,
  author = {Fedik, Nikita and Nebgen, Benjamin and Lubbers, Nicholas and Barros, Kipton and Kulichenko, Maksim and Li, Ying Wai and Zubatyuk, Roman and Messerly, Richard and Isayev, Olexandr and Tretiak, Sergei},
  title = {Synergy of semiempirical models and machine learning in computational chemistry},
  year = {2023},
  journal = {The Journal of Chemical Physics},
  volume = {159},
  number = {11},
  doi = {10.1063/5.0151833},
  url = {http://dx.doi.org/10.1063/5.0151833},
  publisher = {AIP Publishing},
  keywords = {semi-empirical methods, machine learning, hybrid quantum chemistry, computational chemistry, method synergy},
  researchAreas = {quantum-chemistry, ml-potentials, ai-for-science},
  citations = {18}
}