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Title: A Bayesian framework for adaptive selection, calibration, and validation of coarse-grained models of atomistic systems

Authors:
; ; ORCiD logo
Publication Date:
Type:
Publisher's Accepted Manuscript
Journal Name:
Journal of Computational Physics
Additional Journal Information:
Journal Name: Journal of Computational Physics Journal Volume: 295 Journal Issue: C; Journal ID: ISSN 0021-9991
Publisher:
Elsevier
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
OSTI Identifier:
1367757

Farrell, Kathryn, Oden, J. Tinsley, and Faghihi, Danial. A Bayesian framework for adaptive selection, calibration, and validation of coarse-grained models of atomistic systems. United States: N. p., Web. doi:10.1016/j.jcp.2015.03.071.
Farrell, Kathryn, Oden, J. Tinsley, & Faghihi, Danial. A Bayesian framework for adaptive selection, calibration, and validation of coarse-grained models of atomistic systems. United States. doi:10.1016/j.jcp.2015.03.071.
Farrell, Kathryn, Oden, J. Tinsley, and Faghihi, Danial. 2015. "A Bayesian framework for adaptive selection, calibration, and validation of coarse-grained models of atomistic systems". United States. doi:10.1016/j.jcp.2015.03.071.
@article{osti_1367757,
title = {A Bayesian framework for adaptive selection, calibration, and validation of coarse-grained models of atomistic systems},
author = {Farrell, Kathryn and Oden, J. Tinsley and Faghihi, Danial},
abstractNote = {},
doi = {10.1016/j.jcp.2015.03.071},
journal = {Journal of Computational Physics},
number = C,
volume = 295,
place = {United States},
year = {2015},
month = {8}
}