Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning.
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%0 Journal Article
%1 journals/corr/abs-2205-15510
%A Sun, Jiace
%A Cheng, Lixue
%A III, Thomas F. Miller
%D 2022
%J CoRR
%K dblp
%T Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning.
%U http://dblp.uni-trier.de/db/journals/corr/corr2205.html#abs-2205-15510
%V abs/2205.15510
@article{journals/corr/abs-2205-15510,
added-at = {2022-06-01T00:00:00.000+0200},
author = {Sun, Jiace and Cheng, Lixue and III, Thomas F. Miller},
biburl = {https://www.bibsonomy.org/bibtex/2d39607688f9a9b1911be4b28a7772c08/dblp},
ee = {https://doi.org/10.48550/arXiv.2205.15510},
interhash = {4c307886ca24df18adc3e087efc7a75e},
intrahash = {d39607688f9a9b1911be4b28a7772c08},
journal = {CoRR},
keywords = {dblp},
timestamp = {2024-04-08T22:06:02.000+0200},
title = {Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning.},
url = {http://dblp.uni-trier.de/db/journals/corr/corr2205.html#abs-2205-15510},
volume = {abs/2205.15510},
year = 2022
}
