Machine Learning of Coarse-Grained Molecular Dynamics Force Fields

@article{Wang2018MachineLO,
  title={Machine Learning of Coarse-Grained Molecular Dynamics Force Fields},
  author={Jiang Wang and Christoph Wehmeyer and Frank No{\'e} and Cecilia Clementi},
  journal={ACS Central Science},
  year={2018},
  volume={5},
  pages={755 - 767}
}
Atomistic or ab initio molecular dynamics simulations are widely used to predict thermodynamics and kinetics and relate them to molecular structure. A common approach to go beyond the time- and length-scales accessible with such computationally expensive simulations is the definition of coarse-grained molecular models. Existing coarse-graining approaches define an effective interaction potential to match defined properties of high-resolution models or experimental data. In this paper, we… 
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