🏆 A ranked list of awesome atomistic machine learning libraries ⚛️🧬💎.

Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.

AMPtorch: Atomistic Machine Learning Package (AMP) - PyTorch

Data mining for materials science

Discover app of MC3D developed with react.js

Fast Numba-enabled CPU and GPU computations of Earth Mover's (scipy.stats.wasserstein_distance) and Euclidean distances.

ChemNLP project

On-the-fly generator of space-group irreducible representations

MatBench: Benchmark for materials science property prediction

Registry for BIG-MAP apps and codes.

XRay Estimation and Refinement Using Similarity (XERUS)

Public development project of the LAMMPS MD software package

A python wrapper for programatically accessing ChemInventory

A conda-smithy repository for optimade.

Registry of schemas that use LinkML

A high performance mapping class to construct ElM2D plots from large datasets of inorganic compositions.

Official Repository of the Optados code

FastAPI framework, high performance, easy to learn, fast to code, ready for production

Data repository accompanying De Breuck et al., "Robust model benchmarking and bias-imbalance in data-driven materials science: a case study on MODNet"

A suite of computational materials science tools.

Interface with AiiDA to automate CASTEP calculations and preserve their provenance.

GitHub Pages repository for EMMO releases and documentation

Reading binary files generated by CASTEP in Python

Jupyter Notebook Conversion