ilyes319 / mace-tutorialsLinks
Collection of tutorials to use the MACE machine learning force field.
☆48Updated last year
Alternatives and similar repositories for mace-tutorials
Users that are interested in mace-tutorials are comparing it to the libraries listed below
Sorting:
- ☆30Updated this week
- Active Learning for Machine Learning Potentials☆58Updated last month
- Collection of Tutorials on Machine Learning Interatomic Potentials☆22Updated last year
- ☆94Updated this week
- ☆26Updated last month
- GRACE models and gracemaker (as implemented in TensorPotential package)☆73Updated 2 weeks ago
- Quick Uncertainty and Entropy via STructural Similarity☆49Updated this week
- Particle-mesh based calculations of long-range interactions in PyTorch☆60Updated last week
- Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics https://openreview.net/foru…☆68Updated 2 weeks ago
- train and use graph-based ML models of potential energy surfaces☆106Updated last week
- Alchemical machine learning interatomic potentials☆32Updated 10 months ago
- LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials☆52Updated 2 weeks ago
- PhaseForge is a framework for high-throughput alloy phase diagram prediction using machine learning interatomic potentials (MLIPs) integr…☆46Updated 3 weeks ago
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆95Updated last month
- OVITO Python modifier to compute the Warren-Cowley parameters.☆33Updated 6 months ago
- A unified platform for fine-tuning atomistic foundation models in chemistry and materials science☆60Updated last week
- A foundational potential energy dataset for materials☆42Updated last month
- Symmetry-Adapted Learning of Three-dimensional Electron Densities (and their electrostatic response)☆40Updated 4 months ago
- Code for automated fitting of machine learned interatomic potentials.☆125Updated this week
- Python package to interact with high-dimensional representations of the chemical elements☆44Updated last week
- ☆28Updated 2 months ago
- A molecular simulation package integrating MLFFs in MOFs for DAC☆36Updated last month
- “Ab initio thermodynamics of liquid and solid water” Bingqing Cheng, Edgar A. Engel, JÖrg Behler, Christoph Dellago and Michele Ceriotti…☆27Updated 5 years ago
- MACE_Osaka24 models☆18Updated 9 months ago
- Computing representations for atomistic machine learning☆73Updated 2 weeks ago
- Benchmarking foundation Machine Learning Potentials with Lattice Thermal Conductivity from Anharmonic Phonons☆16Updated 11 months ago
- A framework for performing active learning for training machine-learned interatomic potentials.☆39Updated last week
- A python library for calculating materials properties from the PES☆121Updated this week
- ☆20Updated 11 months ago
- A text-guided diffusion model for crystal structure generation☆64Updated 4 months ago