Luthaf / vesinLinks
Compute neighbor lists for atomistic systems
☆73Updated this week
Alternatives and similar repositories for vesin
Users that are interested in vesin are comparing it to the libraries listed below
Sorting:
- 🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics …☆88Updated 2 weeks ago
- Computing representations for atomistic machine learning☆76Updated this week
- Quick Uncertainty and Entropy via STructural Similarity☆56Updated last month
- Train, fine-tune, and manipulate machine learning models for atomistic systems☆54Updated this week
- ☆42Updated 2 weeks ago
- Alchemical machine learning interatomic potentials☆33Updated last year
- ☆22Updated last year
- Particle-mesh based calculations of long-range interactions in PyTorch☆70Updated last week
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆96Updated last week
- ⚛ download and manipulate atomistic datasets☆48Updated 2 months ago
- Collection of tutorials to use the MACE machine learning force field.☆52Updated 2 weeks ago
- Atomistic machine learning models you can use everywhere for everything☆33Updated this week
- Library for Crystal Symmetry in Rust☆69Updated this week
- python workflow toolkit☆43Updated last month
- ☆19Updated 2 years ago
- Collection of Tutorials on Machine Learning Interatomic Potentials☆25Updated last year
- Cross-platform Optimizer for ML Interatomic Potentials☆23Updated 5 months ago
- MACE_Osaka24 models☆25Updated last year
- PhaseForge is a framework for high-throughput alloy phase diagram prediction using machine learning interatomic potentials (MLIPs) integr…☆58Updated 3 months ago
- ☆32Updated last week
- Deprecated - see `pair_nequip_allegro`☆44Updated 9 months ago
- Symmetry-Adapted Learning of Three-dimensional Electron Densities (and their electrostatic response)☆41Updated this week
- Particle-mesh based calculations of long-range interactions in JAX☆23Updated last week
- Display and Edit Molecules (https://zndraw.icp.uni-stuttgart.de)☆49Updated this week
- Heat-conductivity benchmark test for foundational machine-learning potentials☆29Updated last week
- Active Learning for Machine Learning Potentials☆63Updated last week
- ☆118Updated this week
- ☆11Updated last year
- ☆23Updated 2 years ago
- Training Neural Network potentials through customizable routines in JAX.☆61Updated 6 months ago