MLatom 2: An Integrative Platform for Atomistic Machine Learning

Atomistic machine learning (AML) simulations are used in chemistry at an ever-increasing pace. A large number of AML models has been developed, but their implementations are scattered among different packages, each with its own conventions for input and output. Thus, here we give an overview of our...

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Detalles Bibliográficos
Autores principales: Dral, Pavlo O., Ge, Fuchun, Xue, Bao-Xin, Hou, Yi-Fan, Pinheiro, Max, Huang, Jianxing, Barbatti, Mario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8187220/
https://www.ncbi.nlm.nih.gov/pubmed/34101036
http://dx.doi.org/10.1007/s41061-021-00339-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8187220/
https://www.ncbi.nlm.nih.gov/pubmed/34101036
http://dx.doi.org/10.1007/s41061-021-00339-5

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