Machine Learning of Parameters for Accurate Semiempirical Quantum Chemical Calculations

[Image: see text] We investigate possible improvements in the accuracy of semiempirical quantum chemistry (SQC) methods through the use of machine learning (ML) models for the parameters. For a given class of compounds, ML techniques require sufficiently large training sets to develop ML models that...

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Detalles Bibliográficos
Autores principales: Dral, Pavlo O., von Lilienfeld, O. Anatole, Thiel, Walter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2015
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4479612/
https://www.ncbi.nlm.nih.gov/pubmed/26146493
http://dx.doi.org/10.1021/acs.jctc.5b00141

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4479612/
https://www.ncbi.nlm.nih.gov/pubmed/26146493
http://dx.doi.org/10.1021/acs.jctc.5b00141

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