Open-Catalyst-Project / ocpapiLinks
☆15Updated last year
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
- ☆22Updated last year
- Robust NN MD simulator☆21Updated 2 years ago
- The course materials for "Machine Learning in Chemistry 101"☆84Updated 5 years ago
- Reference implementation of "SpookyNet: Learning force fields with electronic degrees of freedom and nonlocal effects"☆85Updated 3 years ago
- [NeurIPS 2024] Official implementation of the Efficiently Scaled Attention Interatomic Potential☆57Updated 4 months ago
- Alchemical machine learning interatomic potentials☆33Updated last year
- Code for performing adversarial attacks on atomistic systems using NN potentials☆40Updated 3 years ago
- Collection of tutorials to use the MACE machine learning force field.☆51Updated 2 weeks ago
- Reference implementation of "Ewald-based Long-Range Message Passing for Molecular Graphs" (ICML 2023)☆51Updated 2 years ago
- pytorch implementation of dftd2 & dftd3 (not actively maintained)☆91Updated 3 weeks ago
- Code Repository for "Direct prediction of phonon density of states with Euclidean neural network"☆28Updated 3 years ago
- tools for machine learning in condensed matter physics and quantum chemistry☆33Updated 3 years ago
- A software for automating materials science computations☆33Updated 3 months ago
- ☆35Updated 4 months ago
- Split a MOF into its building blocks.☆25Updated 3 years ago
- Generative materials benchmarking metrics, inspired by guacamol and CDVAE.☆41Updated last year
- This repo contains the datasets used for the paper The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials.☆19Updated 3 years ago
- [NeurIPS 2024] source code for "A Recipe for Charge Density Prediction"☆39Updated last year
- A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.☆45Updated last year
- [ICML'24] Adsorbate Placement via Conditional Denoising Diffusion☆23Updated last year
- 🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics …☆88Updated last week
- Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting☆36Updated last year
- Workflow for creating and analyzing the Open Catalyst Dataset☆123Updated last year
- Point Edge Transformer☆33Updated 4 months ago
- ☆26Updated 3 years ago
- A framework for performing active learning for training machine-learned interatomic potentials.☆39Updated 2 months ago
- Active Learning for Machine Learning Potentials☆63Updated this week
- [npj Comp. Mat.] Higher-order equivariant neural networks for charge density prediction in materials☆71Updated 11 months ago
- Corresponding dataset and tools for the AdsorbML manuscript.☆43Updated last year