How to do impactful research in artificial intelligence for chemistry and materials science

Austin Cheng, Cher Tian Ser, Marta Skreta, Andrés Guzmán-Cordero, Luca Thiede, Andreas Burger, Abdulrahman Aldossary, Shi Xuan Leong, Sergio Pablo-García, Felix Strieth-Kalthoff, Alán Aspuru-Guzik
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Abstract

Machine learning has been pervasively touching many fields of science. Chemistry and materials science are no exception. While machine learning has been making a great impact, it is still not reaching its full potential or maturity. In this perspective, we first outline current applications across a diversity of problems in chemistry. Then, we discuss how machine learning researchers view and approach problems in the field. Finally, we provide our considerations for maximizing impact when researching machine learning for chemistry.
如何在化学和材料科学领域开展有影响力的人工智能研究
机器学习已经渗透到许多科学领域,化学和材料科学也不例外。化学和材料科学也不例外。虽然机器学习已经产生了巨大影响,但其潜力和成熟度仍未充分发挥出来。在本视角中,我们首先概述了当前在化学领域各种问题中的应用。然后,我们讨论机器学习研究人员如何看待和处理该领域的问题。最后,我们提出了在研究化学机器学习时如何最大化其影响力的几点考虑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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