文献
J-GLOBAL ID:201902254615263867
整理番号:19A0659942
ハイブリッドDFT誤差より低い分子機械学習モデルの予測誤差【JST・京大機械翻訳】
Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error
著者 (10件):
Faber Felix A.
(Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials, Department of Chemistry, University of Basel, Switzerland)
,
Hutchison Luke
(California, United States)
,
Huang Bing
(Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials, Department of Chemistry, University of Basel, Switzerland)
,
Gilmer Justin
(California, United States)
,
Schoenholz Samuel S.
(California, United States)
,
Dahl George E.
(California, United States)
,
Vinyals Oriol
(U.K.)
,
Kearnes Steven
(California, United States)
,
Riley Patrick F.
(California, United States)
,
von Lilienfeld O. Anatole
(Institute of Physical Chemistry and National Center for Computational Design and Discovery of Novel Materials, Department of Chemistry, University of Basel, Switzerland)
資料名:
Journal of Chemical Theory and Computation
(Journal of Chemical Theory and Computation)
巻:
13
号:
11
ページ:
5255-5264
発行年:
2017年
JST資料番号:
W2328A
ISSN:
1549-9618
CODEN:
JCTCCE
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)