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Graphormer

Graphormer is a deep learning package that allows researchers and developers to train custom models for molecule modeling tasks. It aims to accelerate the research and application in AI for molecule science, such as material design, drug discovery, etc.

matbench

Matbench: Benchmarks for materials science property prediction

cp2k-input-tools

Fully validating pure-python CP2K input file tools including preprocessing capabilities

GPUMD

Graphics Processing Units Molecular Dynamics

atb2lammps

Convert files from the ATB repository to LAMMPS format

REANN

Collection_of_Frequency_Scale_Factors

A collection of frequency scale factors from various sources.

ML-notes

notes about machine learning

ParmEd

Parameter/topology editor and molecular simulator

LAMMPS_tutorials_for_short_courses

Required LAMMPS and MATLAB files for several molecular dynamics simulations.

MDBrushAnalysis

Library of Python classes for parsing LAMMPS density profiles and data files, and specifically for post-processing of MD simulations of polymer brushes in equilibrium with solvent vapours.

poster_template

some academic posters as references. May we have in-person poster session soon!

XenonPy

XenonPy is a Python Software for Materials Informatics

pytorch_learn

learn the pytorch

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

MaterialsStudio_PerlScript

ccgnet

pymatgen

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project.

XGraphBoost

ProgrammingProjects

C++ Programming Tutorial in Chemistry

numpy-ml

Machine learning, in numpy

clandpol

Polarisable force field for ionic liquids

studynotes

geo_analysis

GRO2LAM

Gromacs to Lammps simulation converter

dlwpt-code

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

pytorch-template

PyTorch deep learning projects made easy.

mltools

Code-Collection for Machine-Learning applications

viparr

Parameterize chemical systems for Desmond and Anton.

Deep-Learning-from-Scratch

Deep Learning from Scratch book notes