领域(数学)
计算机科学
数据科学
表征(材料科学)
人工智能
领域(数学分析)
认知科学
纳米技术
机器学习
心理学
材料科学
数学
数学分析
纯数学
作者
Keith T. Butler,Daniel W. Davies,Hugh M. Cartwright,Olexandr Isayev,Aron Walsh
出处
期刊:Nature
[Springer Nature]
日期:2018-07-01
卷期号:559 (7715): 547-555
被引量:3022
标识
DOI:10.1038/s41586-018-0337-2
摘要
Here we summarize recent progress in machine learning for the chemical sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future in which the design, synthesis, characterization and application of molecules and materials is accelerated by artificial intelligence. Recent progress in machine learning in the chemical sciences and future directions in this field are discussed.
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