Balancing data for generalizable machine learning to predict glass-forming ability of ternary alloys (Journal Article) | NSF PAGES

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Citation Details

Balancing data for generalizable machine learning to predict glass-forming ability of ternary alloys

Authors:: Yao, Yi; Sullivan, Timothy; Yan, Feng; Gong, Jiaqi; Li, Lin

Award ID(s):: 1727875

Publication Date:: 2022-03-01

NSF-PAR ID:: 10379599

Journal Name:: Scripta Materialia

Volume:: 209

Issue:: C

Page Range or eLocation-ID:: 114366

ISSN:: 1359-6462

Sponsoring Org:: National Science Foundation

Free Publicly Accessible Full Text
Accepted Manuscript1.0
Publisher's Version of Record
https://doi.org/10.1016/j.scriptamat.2021.114366