Collection of Tutorials on Machine Learning Interatomic Potentials
☆25Jul 26, 2024Updated last year
Alternatives and similar repositories for Tutorials
Users that are interested in Tutorials are comparing it to the libraries listed below
Sorting:
- ☆11Sep 16, 2024Updated last year
- CUDA implementations of MACE models☆23Aug 19, 2025Updated 6 months ago
- Tools for geometric learning☆12Sep 26, 2025Updated 5 months ago
- ☆15Oct 1, 2023Updated 2 years ago
- 🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics …☆90Updated this week
- ☆42Feb 13, 2026Updated 2 weeks ago
- Benchmarking foundation Machine Learning Potentials with Lattice Thermal Conductivity from Anharmonic Phonons☆16Oct 30, 2024Updated last year
- Collection of tutorials to use the MACE machine learning force field.☆53Jan 22, 2026Updated last month
- Machine Learning Interatomic Potentials with the Atomic Cluster Expansion☆70Jan 6, 2026Updated last month
- MESS: Modern Electronic Structure Simulations☆20Sep 24, 2024Updated last year
- Official repository for the paper "Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials".☆21Oct 29, 2024Updated last year
- Compute neighbor lists for atomistic systems☆74Updated this week
- ☆119Feb 10, 2026Updated 2 weeks ago
- Auto-differentiated descriptors using Enzyme☆12Apr 2, 2025Updated 10 months ago
- Implementation of various equivariant models in JAX☆12Apr 12, 2024Updated last year
- Calculation of vibrational spectra with quantum nuclear motion☆12Sep 18, 2024Updated last year
- ☆32Feb 2, 2026Updated 3 weeks ago
- A collection of simulation recipes for the atomic-scale modeling of materials and molecules☆35Feb 20, 2026Updated last week
- ☆12Feb 15, 2026Updated last week
- ☆16Feb 17, 2025Updated last year
- Quantifying Pairwise Chemical Similarity for Polymers☆15Jan 23, 2024Updated 2 years ago
- MACE foundation models (MP, OMAT, mh-1)☆203Updated this week
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆96Jan 28, 2026Updated last month
- Local Environment-based Atomic Features☆13Dec 19, 2024Updated last year
- ☆12May 10, 2024Updated last year
- Lab materials for MIT 3.320 and Harvard AP 275 courses on atomistic modeling☆15Apr 20, 2021Updated 4 years ago
- Particle-mesh based calculations of long-range interactions in PyTorch☆76Jan 29, 2026Updated last month
- python workflow toolkit☆43Dec 23, 2025Updated 2 months ago
- This repository contains the source code for Bayesian Learned Interatomic Potentials (BLIP)☆31Aug 20, 2025Updated 6 months ago
- JAX implementation of the NequIP neural network interatomic potential☆16Updated this week
- Deep Coarse-grained Potentials via Relative Entropy Minimization☆18Feb 22, 2023Updated 3 years ago
- An LLM system for the ultra-accurate (TPR=98.8%) prediction of the synthesizability and precursors of crystal structures☆38Mar 13, 2025Updated 11 months ago
- MACE-OFF23 models☆60Jan 29, 2025Updated last year
- jax library for E3 Equivariant Neural Networks☆224Aug 25, 2025Updated 6 months ago
- A RL framework for Crystal Structure Generation using GRPO☆38Feb 8, 2026Updated 2 weeks ago
- Reproduction of CGCNN for predicting material properties☆23Feb 2, 2026Updated 3 weeks ago
- A collection of files related to machine learning force fields☆22Oct 25, 2023Updated 2 years ago
- Introductory lectures in atomistic machine learning☆23Jul 9, 2025Updated 7 months ago
- ☆22May 7, 2025Updated 9 months ago