🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
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Updated
May 24, 2024
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
UF3: a python library for generating ultra-fast interatomic potentials
NequIP is a code for building E(3)-equivariant interatomic potentials
A flexible and performant framework for training machine learning potentials.
python library for atomistic machine learning
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
[ICLR'24] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
Generator of polynomial machine learning potentials
A Python library and command line interface for automated free energy calculations
An open source Julia library for active learning of interatomic potentials in atomistic simulations of materials. It incorporates elements of bayesian inference, machine learning, differentiable programming, software composability, and high-performance computing.
KIM-based Learning-Integrated Fitting Framework for interatomic potentials.
A Python package for developing machine learning interatomic potentials, based on JAX.
A python package for fast building amorphous solids and liquid mixtures from https://materialsproject.org computed structures and machine learning interatomic potentials
FLAME: a library for atomistic modeling environments
Impliment of the ReaxFF-nn mathine learning potential in the GULP package
Instructions and scripts for adaptive sampling for gas-surface dynamics
A parallel molecular dynamics simulation algorithm for studying the thermal stability of nanoalloys.
[ICLR'23 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
An attempt to fit ab-initio materials database (e.g. Materials Project) results to FitSNAP potential.
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