Stars
Atomistic machine learning models you can use everywhere for everything
Domain specific library for electronic structure calculations
Python toolkit for molecular dynamics analysis
A Curated Dataset of Crystal Structures and Experimentally Measured Ionic Conductivities for Lithium Solid-State Electrolytes
Universal interatomic potentials for advanced materials modeling
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
Particle-mesh based calculations of long-range interactions in JAX
Train, fine-tune, and manipulate machine learning models for atomistic systems
Particle-mesh based calculations of long-range interactions in PyTorch
Computing representations for atomistic machine learning
Sample codes for my book on molecular dynamics simulation
A collection of simulation recipes for the atomic-scale modeling of materials and molecules
An open-source Python package for creating fast and accurate interatomic potentials.
DFTB+ general package for performing fast atomistic simulations
bananenpampe / equisolve
Forked from lab-cosmo/equisolveA package tasked with taking equistore objects and computing machine learning models using them.
The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field
A collection of scikit-learn compatible utilities that implement methods born out of the materials science and chemistry communities
Jupyter notebooks for the lectures of the Introduction to Atomistic Modeling
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Multi-language library for the calculation of spherical harmonics in Cartesian coordinates
An Open Source Machine Learning Framework for Everyone
Tensors and Dynamic neural networks in Python with strong GPU acceleration
A library of ultrasoft and PAW pseudopotentials
A Python package for manipulating atomistic data of software in computational science