most citedNeuroevolution machine learning potentials: Combining high accuracy and low cost in atomistic simulations and application to heat transport

526 citations · 526 across the 1 of their papers we have counts for

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1 paper

physics.comp-ph2021★ 526 cited

Neuroevolution machine learning potentials: Combining high accuracy and low cost in atomistic simulations and application to heat transport

Zheyong Fan, Zezhu Zeng, Cunzhi Zhang +4

We develop a neuroevolution-potential (NEP) framework for generating neural network based machine-learning potentials. They are trained using an evolutionary strategy for performin…