williamratcliff / GNN-tutorial-APS-March-2023Links
These are the slides associated with the GNN tutorial at the APS March Meeting
☆21Updated 2 years ago
Alternatives and similar repositories for GNN-tutorial-APS-March-2023
Users that are interested in GNN-tutorial-APS-March-2023 are comparing it to the libraries listed below
Sorting:
- Unsupervised learning of atomic scale dynamics from molecular dynamics.☆81Updated 3 years ago
- This repo contains the datasets used for the paper The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials.☆19Updated 2 years ago
- Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting☆32Updated last year
- Input files for Batzner, S., Musaelian, A., Sun, L., Geiger, M., Mailoa, J. P., Kornbluth, M., ... & Kozinsky, B. (2021). E(3)-equivarian…☆13Updated last month
- A Python library for building atomic neural networks☆116Updated 3 months ago
- Official implementation of DeepDFT model☆81Updated 2 years ago
- Official repository for the paper "Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials".☆20Updated 9 months ago
- polyVERSE is a comprehensive repository of informatics-ready datasets curated by the Ramprasad Group.☆20Updated 2 months ago
- An overview of literature that discusses the use of machine learning for atomistic simulations☆45Updated 2 years ago
- Python Suite for Advanced General Ensemble Simulations☆91Updated 2 months ago
- Code for performing adversarial attacks on atomistic systems using NN potentials☆39Updated 2 years ago
- Equivariant machine learning interatomic potentials in JAX.☆74Updated 3 months ago
- ☆32Updated 4 years ago
- Multiobjective active learning with tunable accuracy/efficiency tradeoff and clear stopping criterion.☆40Updated 4 months ago
- ☆22Updated 3 years ago
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆77Updated 3 years ago
- Interactive Jupyter Notebooks for learning the fundamentals of Density-Functional Theory (DFT)☆72Updated last month
- "Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures", Jordan Hoffmann, Louis Maestrati, Yoshihide Sawada, Jian Tang, Je…☆34Updated 5 years ago
- Shared repo for trajectory analysis and infrastructure development☆21Updated last year
- The course materials for "Machine Learning in Chemistry 101"☆79Updated 4 years ago
- A Newtonian message passing network for deep learning of interatomic potentials and forces☆44Updated last month
- Zooming Memory Based Initialization (ZoMBI) algorithm for discovery of optima within challenging needle-in-a-haystack (extreme data imbal…☆17Updated last year
- Generate and predict molecular electron densities with Euclidean Neural Networks☆48Updated last year
- GemNet model in TensorFlow, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)☆26Updated 2 years ago
- AMPtorch: Atomistic Machine Learning Package (AMP) - PyTorch☆60Updated 2 years ago
- Deprecated - see `pair_nequip_allegro`☆44Updated 3 months ago
- A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.☆44Updated 11 months ago
- Workflow for creating and analyzing the Open Catalyst Dataset☆110Updated 6 months ago
- The Wren sits on its Roost in the Aviary.☆58Updated last month
- [NeurIPS 2024] source code for "A Recipe for Charge Density Prediction"☆35Updated 7 months ago