teddykoker / nequip-eqxLinks
JAX implementation of the NequIP neural network interatomic potential
☆14Updated last month
Alternatives and similar repositories for nequip-eqx
Users that are interested in nequip-eqx are comparing it to the libraries listed below
Sorting:
- ☆22Updated 4 months ago
- An ASE-friendly implementation of the amorphous-to-crystalline (a2c) workflow.☆11Updated 2 months ago
- Alchemical machine learning interatomic potentials☆32Updated 10 months ago
- CUDA implementations of MACE models☆15Updated 3 weeks ago
- DiffSyn: A Generative Diffusion Approach to Materials Synthesis Planning☆13Updated 4 months ago
- ☆25Updated 2 weeks ago
- MESS: Modern Electronic Structure Simulations☆37Updated last week
- ☆28Updated 2 months ago
- Benchmarking foundation Machine Learning Potentials with Lattice Thermal Conductivity from Anharmonic Phonons☆16Updated 10 months ago
- Atomistic machine learning models you can use everywhere for everything☆22Updated last week
- Compute neighbor lists for atomistic systems☆60Updated last week
- A collection of simulation recipes for the atomic-scale modeling of materials and molecules☆28Updated last week
- ☆14Updated last year
- dataset augmentation for atomistic machine learning☆20Updated 2 months ago
- Training and evaluating machine learning models for atomistic systems.☆42Updated last week
- Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics https://openreview.net/foru…☆63Updated last month
- Particle-mesh based calculations of long-range interactions in JAX☆19Updated 7 months ago
- ☆23Updated last year
- Equivariant machine learning interatomic potentials in JAX.☆75Updated 4 months ago
- Nequix: Training a foundation model for materials on a budget.☆40Updated 2 weeks ago
- ☆21Updated last year
- [NeurIPS 2024] source code for "A Recipe for Charge Density Prediction"☆35Updated 8 months ago
- ☆11Updated 7 months ago
- [TMLR 2025] Stability-Aware Training of Machine Learning Force Fields with Differentiable Boltzmann Estimators☆14Updated 6 months ago
- Reproduction of CGCNN for predicting material properties☆23Updated last week
- Tools for machine learnt interatomic potentials☆37Updated this week
- Vote on whether you think predicted crystal structures could be synthesised☆18Updated last year
- MACE_Osaka24 models☆17Updated 8 months ago
- PhaseForge is a framework for high-throughput alloy phase diagram prediction using machine learning interatomic potentials (MLIPs) integr…☆46Updated this week
- ☆18Updated 2 years ago