Pinned Repositories
alignn_hs
Atomistic Line Graph Neural Network
cdvae
An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]
CS224W_Winter2021
CS224W Stanford Winter 2021 Homework solutions
deepmind_materials_discovery
maml
Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
pymatgen
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.
VaspPoscarMayavi
Use 3D visualization software Mayavi to visualize VASP POSCAR file.
deepmd-kit
A deep learning package for many-body potential energy representation and molecular dynamics
dpgen
The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field
Cheng-JW's Repositories
Cheng-JW/alignn_hs
Atomistic Line Graph Neural Network
Cheng-JW/cdvae
An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]
Cheng-JW/CS224W_Winter2021
CS224W Stanford Winter 2021 Homework solutions
Cheng-JW/deepmind_materials_discovery
Cheng-JW/maml
Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
Cheng-JW/pymatgen
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.
Cheng-JW/VaspPoscarMayavi
Use 3D visualization software Mayavi to visualize VASP POSCAR file.