chc273 Goto Github PK

ase_ani

ANI-1 neural net potential with python interface (ASE)

atomsk

Atomsk: A Tool For Manipulating And Converting Atomic Data Files -

carcnn

Convolutional neural network powered self-driving car model

casmcode

First-principles statistical mechanical software for the study of multi-component crystalline solids

chc273

chc273.github.io

conda

Specifying a conda environment with `environment.yml`

deepmd-kit

A deep learning package for many-body potential energy representation and molecular dynamics

gnn_mrs2022

MRS2022 Tutorial on Graph Neural Network

llm.c

LLM training in simple, raw C/CUDA

materials-databases

materialsdata

A collection of materials data for machine learning purposes

matsim

Material simulation toolkits and tutorials

mdcluster

Density-based clustering of trajectories

mep

Minimum energy path tools for atomistic simulations

miworkshop

Materials for Workshop on Materials Informatics

ml_material_tutorials

Tutorials of applying machine learning models to materials

mvl_models

MAVRL models

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.

pymatgen-db

Pymatgen-db provides an addon to the Python Materials Genomics (pymatgen) library (https://pypi.python.org/pypi/pymatgen) that allows the creation of Materials Project-style databases for management of materials data.

quantumresources

A collection of resources for Quantum Computing

semantic-kernel

Integrate cutting-edge LLM technology quickly and easily into your apps

simple-nn

SIMPLE-NN(SNU Interatomic Machine-learning PotentiaL packagE – version Neural Network)

supercon

Data used in "Machine learning modeling of superconducting critical temperature" paper

tensorflow

An Open Source Machine Learning Framework for Everyone

torchani

Accurate Neural Network Potential on PyTorch

tutorials