jla-gardner / graph-pesLinks
train and use graph-based ML models of potential energy surfaces
☆99Updated last week
Alternatives and similar repositories for graph-pes
Users that are interested in graph-pes are comparing it to the libraries listed below
Sorting:
- MACE-OFF23 models☆42Updated 6 months ago
- A text-guided diffusion model for crystal structure generation☆62Updated 2 months ago
- Particle-mesh based calculations of long-range interactions in PyTorch☆53Updated last week
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆89Updated last month
- GRACE models and gracemaker (as implemented in TensorPotential package)☆65Updated last month
- ☆28Updated 2 weeks ago
- ☆88Updated last week
- Collection of tutorials to use the MACE machine learning force field.☆47Updated 10 months ago
- A unified platform for fine-tuning atomistic foundation models in chemistry and materials science☆54Updated last week
- Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics https://openreview.net/foru…☆60Updated 3 weeks ago
- ☆59Updated 2 months ago
- MLP training for molecular systems☆49Updated this week
- Efficient And Fully Differentiable Extended Tight-Binding☆98Updated 3 weeks ago
- ⚛ download and manipulate atomistic datasets☆46Updated 7 months ago
- Higher-order equivariant neural networks for charge density prediction in materials☆59Updated 5 months ago
- Code for automated fitting of machine learned interatomic potentials.☆86Updated this week
- Algorithms to analyze and predict molecular structures☆20Updated 3 weeks ago
- [NeurIPS 2024] Official implementation of the Efficiently Scaled Attention Interatomic Potential☆52Updated 4 months ago
- LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials☆47Updated 2 weeks ago
- Active Learning for Machine Learning Potentials☆56Updated last year
- [ICLR 2025] Official Implementation of "Towards Fast, Specialized Machine Learning Force Fields: Distilling Foundation Models via Energy …☆18Updated 3 months ago
- Official implementation of DeepDFT model☆80Updated 2 years ago
- Generative materials benchmarking metrics, inspired by guacamol and CDVAE.☆40Updated last year
- SO3krates and Universal Pairwise Force Field for Molecular Simulation☆108Updated 2 weeks ago
- Generate and predict molecular electron densities with Euclidean Neural Networks☆48Updated last year
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆77Updated 3 years ago
- A foundational potential energy dataset for materials☆39Updated 3 weeks ago
- ☆18Updated 9 months ago
- scalable molecular simulation☆137Updated last month
- Chemical intuition for surface science in a package.☆36Updated last week