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Madin et al., 2022 - Google Patents

Bayesian-inference-driven model parametrization and model selection for 2CLJQ fluid models

Madin et al., 2022

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Document ID
14609493297750728260
Author
Madin O
Boothroyd S
Messerly R
Fass J
Chodera J
Shirts M
Publication year
Publication venue
Journal of chemical information and modeling

External Links

Snippet

A high level of physical detail in a molecular model improves its ability to perform high accuracy simulations but can also significantly affect its complexity and computational cost. In some situations, it is worthwhile to add complexity to a model to capture properties of …
Continue reading at pmc.ncbi.nlm.nih.gov (PDF) (other versions)

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