98 citations · 98 across the 2 of their papers we have counts for
2 papers
physics.chem-ph2021
REANN: A PyTorch-based End-to-End Multi-functional Deep Neural Network Package for Molecular, Reactive and Periodic Systems
Yaolong Zhang, Junfan Xia, Bin Jiang
In this work, we present a general purpose deep neural network package for representing energies, forces, dipole moments, and polarizabilities of atomistic systems. This so-called…
physics.chem-ph2021★ 98 cited
Physically Motivated Recursively Embedded Atom Neural Networks: Incorporating Local Completeness and Nonlocality
Yaolong Zhang, Junfan Xia, Bin Jiang
Recent advances in machine-learned interatomic potentials largely benefit from the atomistic representation and locally invariant many-body descriptors. It was however recently arg…