Ju Huang's Projects
A curated list of awesome ggplot2 tutorials, packages etc.
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
How to become a deep learning engineer from scratch
Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov
Deep neural networks for density functional theory Hamiltonian.
A deep learning package for many-body potential energy representation and molecular dynamics
A python library to parse, operate and present datasets generated by density functional theory codes
A modular framework for neural networks with Euclidean symmetry
DEPRECATED. Charge equilibration method for crystal structures
Config files for my GitHub profile.
automatic generation of LAMMPS input files for molecular dynamics simulations of MOFs
MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.
MACE-MP models
Stylesheets for Matplotlib
A script to build reference datasets for training neural network potentials from given LAMMPS trajectories.
A collection of files related to machine learning force fields
Basic sanity checks for MOFs.
molSimplify code
Band structure of bulk 2H-phase MoS2
"Cyberpunk style" for matplotlib plots
Parallel t-SNE implementation with Python and Torch wrappers.
Open Catalyst Project's library of machine learning methods for catalysis
Open Babel is a chemical toolbox designed to speak the many languages of chemical data.
The Open Babel website https://openbabel.org
Notes and tutorials on density functional theory calculation using OpenMX.
Explore something new
Python library for the construction of porous materials using topology and building blocks.
open data sets for machine learning pertaining to porous materials
Painlessly create beautiful matplotlib plots.
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