blondegeek / e3nn_symm_breakingLinks
Code repository for "Finding symmetry breaking order parameters with Euclidean Neural Networks"
☆14Updated 4 years ago
Alternatives and similar repositories for e3nn_symm_breaking
Users that are interested in e3nn_symm_breaking are comparing it to the libraries listed below
Sorting:
- ESI-DCAFM-TACO-VDSP Summer School on "Machine Learning for Materials Hard and Soft"☆39Updated 2 years ago
- e3nn tutorial for Materials Research Society Fall Meeting 2021☆12Updated 3 years ago
- Robust NN MD simulator☆20Updated last year
- Steerable E(3) GNN in jax☆24Updated last year
- Reference implementation of "Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions" (ICLR, 2022) and "Sampling-f…☆30Updated last year
- Python code for the paper Bayesian Optimization of Nanoporous Materials.☆24Updated 2 years ago
- Huxel: Huckel model + JAX (parameter optimization)☆10Updated 2 years ago
- Code for performing adversarial attacks on atomistic systems using NN potentials☆38Updated 2 years ago
- Supporting code for "Autoregressive neural-network wavefunctions for ab initio quantum chemistry".☆40Updated 3 years ago
- These are the slides associated with the GNN tutorial at the APS March Meeting☆21Updated 2 years ago
- Pytorch implement of the paper Neural Canonical Transformation with Symplectic Flows☆29Updated 5 years ago
- Input files for Batzner, S., Musaelian, A., Sun, L., Geiger, M., Mailoa, J. P., Kornbluth, M., ... & Kozinsky, B. (2021). E(3)-equivarian…☆13Updated 3 years ago
- ☆10Updated 4 years ago
- A package for density functional approximation using machine learning.☆26Updated 4 years ago
- ☆25Updated 2 years ago
- ☆32Updated 4 years ago
- Equivariant machine learning interatomic potentials in JAX.☆73Updated 2 months ago
- GemNet model in TensorFlow, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆26Updated 2 years ago
- This repo contains the datasets used for the paper The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials.☆18Updated 2 years ago
- Nomalizing flows for orbita-free DFT☆10Updated 9 months ago
- DeepErwin is a python 3.8+ package that implements and optimizes JAX 2.x wave function models for numerical solutions to the multi-electr…☆56Updated 2 months ago
- Official repository for the paper "Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials".☆21Updated 7 months ago
- Implementation of a machine learned density functional☆35Updated last year
- ☆23Updated last year
- A fully autodifferentiable and variational HF☆42Updated 5 years ago
- Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting☆31Updated last year
- ☆22Updated last month
- Generative deep learning model for inorganic materials☆18Updated 2 years ago
- Amons-based quantum machine learning for quantum chemistry☆24Updated 3 years ago
- [TMLR 2025] Stability-Aware Training of Machine Learning Force Fields with Differentiable Boltzmann Estimators☆14Updated 4 months ago