Open-Catalyst-Project / ocpapiLinks
☆15Updated 8 months ago
Alternatives and similar repositories for ocpapi
Users that are interested in ocpapi are comparing it to the libraries listed below
Sorting:
- AMPtorch: Atomistic Machine Learning Package (AMP) - PyTorch☆61Updated 2 years ago
- [ICML'24] Adsorbate Placement via Conditional Denoising Diffusion☆20Updated last year
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆79Updated 3 years ago
- Force-field-enhanced Neural Networks optimized library☆59Updated last month
- Collection of tutorials to use the MACE machine learning force field.☆48Updated last year
- pytorch implementation of dftd2 & dftd3 (not actively maintained)☆84Updated 11 months ago
- Workflow for creating and analyzing the Open Catalyst Dataset☆114Updated 8 months ago
- ☆21Updated last year
- A framework for performing active learning for training machine-learned interatomic potentials.☆39Updated last month
- Corresponding dataset and tools for the AdsorbML manuscript.☆41Updated 8 months ago
- Code Repository for "Direct prediction of phonon density of states with Euclidean neural network"☆28Updated 3 years ago
- The course materials for "Machine Learning in Chemistry 101"☆82Updated 5 years ago
- [NeurIPS 2024] Official implementation of the Efficiently Scaled Attention Interatomic Potential☆54Updated last month
- [NeurIPS'25 AI4Mat] Nequix: Training a foundation model for materials on a budget.☆46Updated this week
- Alchemical machine learning interatomic potentials☆31Updated 11 months ago
- ☆34Updated last month
- ☆23Updated 2 years ago
- Point Edge Transformer☆30Updated last month
- Train, fine-tune, and manipulate machine learning models for atomistic systems☆48Updated this week
- Robust NN MD simulator☆20Updated 2 years ago
- A software for automating materials science computations☆33Updated last week
- Active Learning for Machine Learning Potentials☆59Updated 2 months ago
- State-of-the-art generative model for crystal structure prediction and de novo generation of inorganic crystals.☆32Updated 2 months ago
- [NeurIPS 2024] source code for "A Recipe for Charge Density Prediction"☆36Updated 10 months ago
- ☆61Updated last week
- Equivariant machine learning interatomic potentials in JAX.☆78Updated last week
- Reference implementation of "Ewald-based Long-Range Message Passing for Molecular Graphs" (ICML 2023)☆51Updated 2 years ago
- “Ab initio thermodynamics of liquid and solid water” Bingqing Cheng, Edgar A. Engel, JÖrg Behler, Christoph Dellago and Michele Ceriotti…☆28Updated 5 years ago
- Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics https://arxiv.org/abs/2509.…☆77Updated last week
- Code for performing adversarial attacks on atomistic systems using NN potentials☆40Updated 3 years ago