文献
J-GLOBAL ID:202202275093438371
整理番号:22A0886918
グラフ畳込みニューラルネットワークによる固溶体合金の全エネルギーの高速かつ正確な予測【JST・京大機械翻訳】
Fast and Accurate Predictions of Total Energy for Solid Solution Alloys with Graph Convolutional Neural Networks
著者 (5件):
Lupo Pasini Massimiliano
(Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA)
,
Burcul Marko
(Department of Automation and Control Engineering, Politecnico di Milano, Milan, Italy)
,
Reeve Samuel Temple
(Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA)
,
Eisenbach Markus
(National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA)
,
Perotto Simona
(Department of Mathematics, Politecnico di Milano, Milan, Italy)
資料名:
Communications in Computer and Information Science
(Communications in Computer and Information Science)
巻:
1512
ページ:
79-98
発行年:
2022年
JST資料番号:
W5071A
ISSN:
1865-0929
資料種別:
会議録 (C)
記事区分:
原著論文
発行国:
ドイツ (DEU)
言語:
英語 (EN)