atomind-ai / mlip-arena
Fair and transparent benchmark of machine-learned interatomic potentials (MLIPs), beyond basic error metrics
☆56Updated this week
Alternatives and similar repositories for mlip-arena:
Users that are interested in mlip-arena are comparing it to the libraries listed below
- Compute neighbor lists for atomistic systems☆47Updated last week
- GRACE models and gracemaker (as implemented in TensorPotential package)☆47Updated this week
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆71Updated 2 weeks ago
- Particle-mesh based calculations of long-range interactions in PyTorch☆34Updated this week
- ⚛ download and manipulate atomistic datasets☆43Updated 2 months ago
- ☆24Updated 10 months ago
- ☆20Updated 11 months ago
- Benchmarking foundation Machine Learning Potentials with Lattice Thermal Conductivity from Anharmonic Phonons☆15Updated 4 months ago
- A molecular simulation package integrating MLFFs in MOFs for DAC☆24Updated this week
- MACE-OFF23 models☆31Updated last month
- Quick Uncertainty and Entropy via STructural Similarity☆33Updated this week
- python workflow toolkit☆37Updated 2 weeks ago
- Active Learning for Machine Learning Potentials☆51Updated 9 months ago
- Some tutorial-style examples for validating machine-learned interatomic potentials☆32Updated last year
- MACE_Osaka24 models☆14Updated 2 months ago
- Collection of Tutorials on Machine Learning Interatomic Potentials☆18Updated 7 months ago
- A unified platform for fine-tuning atomistic foundation models in chemistry and materials science☆18Updated last week
- ☆12Updated last year
- Collection of tutorials to use the MACE machine learning force field.☆43Updated 5 months ago
- Algorithms to analyze and predict molecular structures☆16Updated 6 months ago
- Computing representations for atomistic machine learning☆66Updated 2 weeks ago
- open data sets for machine learning pertaining to porous materials☆27Updated last year
- Code for automated fitting of machine learned interatomic potentials.☆71Updated this week
- Force-field-enhanced Neural Networks optimized library☆28Updated 2 weeks ago
- Display and Edit Molecules (https://zndraw.icp.uni-stuttgart.de)☆38Updated this week
- A text-guided diffusion model for crystal structure generation☆37Updated 3 weeks ago
- MLP training for molecular systems☆43Updated this week
- Efficient And Fully Differentiable Extended Tight-Binding☆84Updated this week
- Phonons from ML force fields☆17Updated 2 months ago
- Software for evaluating pareto-optimal synthesis pathways☆25Updated 9 months ago