e3nn / e3nn-tutorial-mrs-fall-2021
e3nn tutorial for Materials Research Society Fall Meeting 2021
☆13Updated 3 years ago
Alternatives and similar repositories for e3nn-tutorial-mrs-fall-2021:
Users that are interested in e3nn-tutorial-mrs-fall-2021 are comparing it to the libraries listed below
- ☆18Updated 10 months 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
- tools for machine learning in condensed matter physics and quantum chemistry☆34Updated 2 years ago
- Active learning workflow developed as a part of the upcoming article "Machine Learning Inter-Atomic Potentials Generation Driven by Activ…☆27Updated 3 years ago
- Code Repository for "Direct prediction of phonon density of states with Euclidean neural network"☆27Updated 2 years ago
- Input files for Batzner, S., Musaelian, A., Sun, L., Geiger, M., Mailoa, J. P., Kornbluth, M., ... & Kozinsky, B. (2021). E(3)-equivarian…☆12Updated 2 years ago
- ☆21Updated 5 years ago
- A Newtonian message passing network for deep learning of interatomic potentials and forces☆38Updated 6 months ago
- ☆22Updated last year
- python workflow toolkit☆37Updated last week
- ☆21Updated 2 months ago
- Compute neighbor lists for atomistic systems☆36Updated this week
- Implementing PaiNN in Pytorch Geometric☆13Updated 2 years ago
- Official repository for the paper "Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials".☆14Updated 3 months ago
- ☆31Updated 4 years ago
- Tracking citations of atomistic simulation engines☆19Updated this week
- Symmetry-Adapted Learning of Three-dimensional Electron Densities (and their electrostatic response)☆31Updated this week
- ☆44Updated 7 months ago
- Quick Uncertainty and Entropy via STructural Similarity☆30Updated 3 weeks ago
- Sparse Gaussian Process Potentials☆27Updated 6 months ago
- Code repository for "Finding symmetry breaking order parameters with Euclidean Neural Networks"☆13Updated 4 years ago
- Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting☆31Updated 11 months ago
- Computing representations for atomistic machine learning☆64Updated this week
- A cookbook with recipes for atomic-scale modeling of materials and molecules☆18Updated this week
- GemNet model in TensorFlow, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆25Updated last year
- Predict the electronic structure and atomic properties (potential energy, forces, and stress tensor) of polymers containing N and/or O.☆17Updated 4 months ago
- Moment Invariants Local Atomic Descriptor☆31Updated 5 months ago
- A framework for performing active learning for training machine-learned interatomic potentials.☆31Updated 2 months ago
- Implementation of a machine learned density functional☆36Updated 7 months ago
- ☆11Updated 2 months ago