mir-group / nequip-input-files
Input files for Batzner, S., Musaelian, A., Sun, L., Geiger, M., Mailoa, J. P., Kornbluth, M., ... & Kozinsky, B. (2021). E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials. arXiv preprint arXiv:2101.03164.
☆12Updated 2 years ago
Alternatives and similar repositories for nequip-input-files:
Users that are interested in nequip-input-files are comparing it to the libraries listed below
- This repo contains the datasets used for the paper The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials.☆18Updated 2 years ago
- Official repository for the paper "Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials".☆15Updated 3 months ago
- Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting☆31Updated 11 months ago
- Implementing PaiNN in Pytorch Geometric☆13Updated 2 years ago
- Predict the electronic structure and atomic properties (potential energy, forces, and stress tensor) of polymers containing N and/or O.☆17Updated 5 months ago
- A Newtonian message passing network for deep learning of interatomic potentials and forces☆40Updated 6 months ago
- ☆19Updated 2 years ago
- ☆10Updated 4 years ago
- Training Neural Network potentials through customizable routines in JAX.☆22Updated this week
- Active learning workflow developed as a part of the upcoming article "Machine Learning Inter-Atomic Potentials Generation Driven by Activ…☆27Updated 3 years ago
- ☆22Updated last year
- ☆11Updated 3 months ago
- NN PES for reactions.☆10Updated 2 years ago
- ☆31Updated 4 years ago
- e3nn tutorial for Materials Research Society Fall Meeting 2021☆13Updated 3 years ago
- [NeurIPS 2024] source code for "A Recipe for Charge Density Prediction"☆17Updated 2 months ago
- Code for performing adversarial attacks on atomistic systems using NN potentials☆36Updated 2 years ago
- Equivariant GNN for the prediction of atomic multipoles up to quadrupoles.☆29Updated 2 years ago
- Generate and predict molecular electron densities with Euclidean Neural Networks☆45Updated last year
- python workflow toolkit☆37Updated this week
- Basis set optimization library for quantum chemistry☆34Updated last year
- Generative materials benchmarking metrics, inspired by guacamol and CDVAE.☆35Updated 8 months ago
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆69Updated 2 years ago
- Benchmarking foundation Machine Learning Potentials with Lattice Thermal Conductivity from Anharmonic Phonons☆15Updated 3 months ago
- tools for machine learning in condensed matter physics and quantum chemistry☆34Updated 2 years ago
- Robust NN MD simulator☆20Updated last year
- ☆19Updated 11 months ago
- Collection of Tutorials on Machine Learning Interatomic Potentials☆18Updated 6 months ago
- Collection of tutorials to use the MACE machine learning force field.☆43Updated 5 months ago
- Deep Modeling for Molecular Simulation, two-day virtual workshop, July 7-8, 2022☆50Updated 2 years ago