lab-cosmo / pet-madLinks
A universal interatomic potential for advanced materials modeling
☆71Updated last week
Alternatives and similar repositories for pet-mad
Users that are interested in pet-mad are comparing it to the libraries listed below
Sorting:
- train and use graph-based ML models of potential energy surfaces☆110Updated 2 weeks ago
- Particle-mesh based calculations of long-range interactions in PyTorch☆62Updated last week
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆96Updated last week
- ☆30Updated 3 weeks ago
- A unified platform for fine-tuning atomistic foundation models in chemistry and materials science☆63Updated 2 weeks ago
- Collection of tutorials to use the MACE machine learning force field.☆48Updated last year
- A foundational potential energy dataset for materials☆43Updated 2 weeks ago
- scalable molecular simulation☆137Updated last week
- Code for automated fitting of machine learned interatomic potentials.☆126Updated 2 weeks ago
- Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics https://arxiv.org/abs/2509.…☆77Updated this week
- GRACE models and gracemaker (as implemented in TensorPotential package)☆74Updated last month
- ☆101Updated last week
- ⚛ download and manipulate atomistic datasets☆47Updated last week
- Object-oriented refactoring of the YARP package☆20Updated last month
- A Python software package for saddle point optimization and minimization of atomic systems.☆120Updated last month
- Atomistic machine learning models you can use everywhere for everything☆28Updated last week
- Quick Uncertainty and Entropy via STructural Similarity☆50Updated 3 weeks ago
- Active Learning for Machine Learning Potentials☆59Updated 2 months ago
- MACE-OFF23 models☆48Updated 8 months ago
- MACE_Osaka24 models☆19Updated 10 months ago
- A text-guided diffusion model for crystal structure generation☆64Updated 4 months ago
- PhaseForge is a framework for high-throughput alloy phase diagram prediction using machine learning interatomic potentials (MLIPs) integr…☆48Updated last month
- ☆27Updated last month
- Efficient And Fully Differentiable Extended Tight-Binding☆104Updated this week
- LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials☆53Updated last month
- Symmetry-Adapted Learning of Three-dimensional Electron Densities (and their electrostatic response)☆40Updated 2 weeks ago
- ML potentials via transfer learning☆20Updated 2 months ago
- MLP training for molecular systems☆54Updated last month
- python workflow toolkit☆43Updated last month
- Automated creation and manipulation of Chemical Reaction Networks (CRNs) in heterogeneous catalysis, allowing the evaluation of species a…☆35Updated this week