lab-cosmo / pet-madLinks
A universal interatomic potential for advanced materials modeling
☆88Updated 3 weeks ago
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☆117Updated 3 weeks ago
- Particle-mesh based calculations of long-range interactions in PyTorch☆67Updated 3 weeks ago
- ☆32Updated 3 months ago
- A unified platform for fine-tuning atomistic foundation models in chemistry and materials science☆70Updated last month
- A foundational potential energy dataset for materials☆49Updated last month
- scalable molecular simulation☆138Updated 2 months ago
- Code for automated fitting of machine learned interatomic potentials.☆134Updated this week
- ☆39Updated 3 weeks ago
- ☆113Updated last week
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆96Updated last month
- A Python software package for saddle point optimization and minimization of atomic systems.☆124Updated 3 months ago
- Collection of tutorials to use the MACE machine learning force field.☆50Updated last year
- 🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics …☆87Updated 2 weeks ago
- GRACE models and gracemaker (as implemented in TensorPotential package)☆80Updated 3 weeks ago
- Active Learning for Machine Learning Potentials☆63Updated last month
- MACE-OFF23 models☆58Updated 11 months ago
- ⚛ download and manipulate atomistic datasets☆48Updated last month
- Atomistic machine learning models you can use everywhere for everything☆32Updated this week
- LAMMPS pair styles for NequIP and Allegro deep learning interatomic potentials☆59Updated 3 months ago
- ALCHEMI Toolkit-Ops is a collection of optimized batch kernels to accelerate computational chemistry and material science workflows.☆72Updated 3 weeks ago
- PhaseForge is a framework for high-throughput alloy phase diagram prediction using machine learning interatomic potentials (MLIPs) integr…☆55Updated 2 months ago
- MACE_Osaka24 models☆24Updated last year
- A python library for calculating materials properties from the PES☆129Updated 2 weeks ago
- Efficient And Fully Differentiable Extended Tight-Binding☆111Updated 2 weeks ago
- Automated creation and manipulation of Chemical Reaction Networks (CRNs) in heterogeneous catalysis, allowing the evaluation of species a…☆41Updated 3 weeks ago
- A flexible workflow for on-the-fly learning of interatomic potential models.☆31Updated this week
- Quick Uncertainty and Entropy via STructural Similarity☆55Updated this week
- Python package to interact with high-dimensional representations of the chemical elements☆46Updated 2 weeks ago
- Development versions of the g-xTB method. Final implementation will not happen here but in tblite (https://github.com/tblite/tblite).☆121Updated 4 months ago
- Computing representations for atomistic machine learning☆74Updated this week