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Improving Molecular Dynamics Simulations with Machine Learning

Published on October 13, 2017 by

NCASD Postdoc Gianmarc Grazioli, Lab PI Carter Butts, and Prof. Ioan Andricioaei from the UCI Chemistry Department have published new results showing how the performance of molecular dynamics simulations can be improved with a little help from machine learning.  These results are contained in their forthcoming paper, “Automated Placement of Interfaces in Conformational Kinetics Calculations

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