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Retrospective on a decade of machine learning for chemical discovery

Over the last decade, we have witnessed the emergence of ever more machine learning applications in all aspects of the chemical sciences. Here, we highlight specific achievements of machine learning models in the field of computational chemistry by considering selected studies of electronic structur...

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Detalles Bibliográficos
Autores principales: von Lilienfeld, O. Anatole, Burke, Kieron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7525448/
https://www.ncbi.nlm.nih.gov/pubmed/32994393
http://dx.doi.org/10.1038/s41467-020-18556-9
Descripción
Sumario:Over the last decade, we have witnessed the emergence of ever more machine learning applications in all aspects of the chemical sciences. Here, we highlight specific achievements of machine learning models in the field of computational chemistry by considering selected studies of electronic structure, interatomic potentials, and chemical compound space in chronological order.