Neural networks trained on molecular dynamics data predict equations of state from pair potentials and invert radial distribution functions into pair potentials more accurately than simple Boltzmann inversion.
Coarsegraining in polymer simulation: From the atomistic to the mesoscopic scale and back
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BoltzmaNN: Predicting effective pair potentials and equations of state using neural networks
Neural networks trained on molecular dynamics data predict equations of state from pair potentials and invert radial distribution functions into pair potentials more accurately than simple Boltzmann inversion.