领域(数学)
人工智能
机器学习
计算机科学
工程伦理学
材料科学
管理科学
纳米技术
工程类
数学
纯数学
作者
J. E. Gubernatis,Turab Lookman
标识
DOI:10.1103/physrevmaterials.2.120301
摘要
Much is being currently written about machine learning applied to materials science, but, what is machine learning? It is certainly not physics, chemistry, or materials science, in which case how do these sciences enter? In this Research Update the authors examine what machine learning is and is not, review several applications of machine learning methods for predicting new materials, noting some of the cases where the predictions have been experimentally validated, and illustrate the spectrum of applications possible. The emphasis is on the broader picture where they discuss some newer methods and more importantly reference their successes. Thus, the paper looks more towards the future than to the past, sharing some of the lessons the authors have learned from their own experience in the field.
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