HongjianChen's repositories
interview_python
关于Python的面试题
ALF
A framework for performing active learning for training machine-learned interatomic potentials.
BLOX
BoundLess Objective-free eXploration (BLOX) for discovery of out-of-trend materials
botorch
Bayesian optimization in PyTorch
CaseStudies
Understanding Molecular Simulations: From Algorithms to Applications
chatgpt_academic
科研工作专用ChatGPT拓展，特别优化学术Paper润色体验，支持自定义快捷按钮，支持markdown表格显示，Tex公式双显示，代码显示功能完善，新增本地Python工程剖析功能/自我剖析功能
chgnet
Pretrained universal neural network potential for charge-informed atomistic modeling
cphy
Class materials for computational physics course
CUDA-Programming
Sample codes for my CUDA programming book
DIST-Toolkit
Generate atomic structures for common defects in materials
gpyumd
A Python interface for GPUMD
High-Entropy-Alloys
Generate random alloys and compute various properties.
lammpstutorials.github.io
LAMMPS tutorials for both beginners and advanced users
MaterialsInformatics
MSE5050/7050 Materials Informatics course at the University of Utah
mbGDML
Create, use, and analyze machine learning potentials within the many-body expansion framework.
Modern-CPP-Programming
Modern C++ Programming Course (C++11/14/17/20)
NEP_CPU
CPU version of NEP
numpyro
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
parmoo
Python library for parallel multiobjective simulation optimization
PHYS6350-ComputationalPhysics
Lecture notes and code for the course PHYS6350 Computational Physics at the University of Houston
PySR
High-Performance Symbolic Regression in Python and Julia
TiO2-Water
This repo contains the training data used to train a Deep Neural Network Potential for the TiO2-Water interface
tools
ssrokyz's tools
torchmd
End-To-End Molecular Dynamics (MD) Engine using PyTorch
tutorial-multi-gpu
Efficient Distributed GPU Programming for Exascale, an SC/ISC Tutorial
udlbook
Understanding Deep Learning - Simon J.D. Prince