NequIP is a code for building E(3)-equivariant interatomic potentials
-
Updated
Jun 2, 2024 - Python
NequIP is a code for building E(3)-equivariant interatomic potentials
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
[ICLR'23 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
[ICLR'24] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
python library for atomistic machine learning
UF3: a python library for generating ultra-fast interatomic potentials
A Python library and command line interface for automated free energy calculations
KIM-based Learning-Integrated Fitting Framework for interatomic potentials.
FLAME: a library for atomistic modeling environments
PotentialLearning.jl: Composable Optimization Workflows for Fast and Accurate Interatomic Potentials.
A flexible and performant framework for training machine learning potentials.
Fitting interatomic potential for molecular dynamics
Provide easy-to-use CESMIX-aligned case studies. Integrate the latest developments of the Julia atomistic ecosystem and state-of-the-art tools.
Modified Embedded Atom Method with Bond Order (MEAM-BO) implementation in LAMMPS
Generator of polynomial machine learning potentials
Automatic Differentiation of Interatomic Potentials with Phonons in Julia: ADIP².jl
A python package for fast building amorphous solids and liquid mixtures from https://materialsproject.org computed structures and machine learning interatomic potentials
Webpage for RANN interatomic potential
Instructions and scripts for adaptive sampling for gas-surface dynamics
Add a description, image, and links to the interatomic-potentials topic page so that developers can more easily learn about it.
To associate your repository with the interatomic-potentials topic, visit your repo's landing page and select "manage topics."