research
∙
11/30/2022
Capturing long-range interaction with reciprocal space neural network
Machine Learning (ML) interatomic models and potentials have been widely...
share
research
∙
11/21/2022
Time-reversal equivariant neural network potential and Hamiltonian for magnetic materials
This work presents Time-reversal Equivariant Neural Network (TENN) frame...
research
∙
10/28/2022
Transferable E(3) equivariant parameterization for Hamiltonian of molecules and solids
Machine learning, especially deep learning, can build a direct mapping f...
research
∙
03/06/2022
Graph Neural Network Potential for Magnetic Materials
Machine Learning (ML) interatomic potential has shown its great power in...
research
∙
01/15/2022
Edge-based Tensor prediction via graph neural networks
Message-passing neural networks (MPNN) have shown extremely high efficie...
research
∙
10/02/2021
