211 citations · 434 across the 10 of their papers we have counts for
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cond-mat.mtrl-sci2019★ 35 cited
Simulating lattice thermal conductivity in semiconducting materials using high-dimensional neural network potential
Emi Minamitani, Masayoshi Ogura, Satoshi Watanabe
We demonstrate that a high-dimensional neural network potential (HDNNP) can predict the lattice thermal conductivity of semiconducting materials with an accuracy comparable to that…
physics.comp-ph2019★ 41 cited
Atomic energy mapping of neural network potential
Dongsun Yoo, Kyuhyun Lee, Wonseok Jeong +2
We show that the intelligence of the machine-learning potential arises from its ability to infer the reference atomic-energy function from a given set of total energies. By utilizi…