Restricted-Variance Molecular Geometry Optimization Based on Gradient-Enhanced Kriging

[Image: see text] Machine learning techniques, specifically gradient-enhanced Kriging (GEK), have been implemented for molecular geometry optimization. GEK-based optimization has many advantages compared to conventional—step-restricted second-order truncated expansion—molecular optimization methods....

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Detalles Bibliográficos
Autores principales: Raggi, Gerardo, Galván, Ignacio Fdez., Ritterhoff, Christian L., Vacher, Morgane, Lindh, Roland
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304864/
https://www.ncbi.nlm.nih.gov/pubmed/32374164
http://dx.doi.org/10.1021/acs.jctc.0c00257

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304864/
https://www.ncbi.nlm.nih.gov/pubmed/32374164
http://dx.doi.org/10.1021/acs.jctc.0c00257

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