Library for efficient training and application of Machine Learning Interatomic Potentials (MLIP)
☆82Jan 7, 2026Updated last month
Alternatives and similar repositories for mlip
Users that are interested in mlip 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
- An ASE-friendly implementation of the amorphous-to-crystalline (a2c) workflow.☆18Oct 19, 2025Updated 4 months ago
- This repository contains the source code for Bayesian Learned Interatomic Potentials (BLIP)☆31Aug 20, 2025Updated 6 months ago
- tools for graph-based machine-learning potentials in jax☆26Apr 9, 2024Updated last year
- JAX implementation of the NequIP neural network interatomic potential☆16Updated this week
- Train, fine-tune, and manipulate machine learning models for atomistic systems☆59Updated this week
- ☆42Feb 13, 2026Updated 2 weeks ago
- Reproduction of CGCNN for predicting material properties☆23Feb 2, 2026Updated 3 weeks ago
- ☆13Feb 11, 2025Updated last year
- train and use graph-based ML models of potential energy surfaces☆121Feb 20, 2026Updated last week
- ☆22May 7, 2025Updated 9 months ago
- [NeurIPS'25 AI4Mat] Nequix: Training a foundation model for materials on a budget and [arXiv'26] Phonon fine-tuning (PFT)☆68Updated this week
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆96Jan 28, 2026Updated last month
- ☆35Feb 22, 2026Updated last week
- ☆24Nov 1, 2024Updated last year
- More efficient and faster version of pyscal☆28Jan 27, 2026Updated last month
- ☆16Feb 17, 2025Updated last year
- Equitrain: A Unified Framework for Training and Fine-tuning Machine Learning Interatomic Potentials☆11Jan 28, 2026Updated last month
- Cross-platform Optimizer for ML Interatomic Potentials☆23Aug 31, 2025Updated 6 months ago
- MESS: Modern Electronic Structure Simulations☆43Sep 26, 2025Updated 5 months ago
- Computing representations for atomistic machine learning☆78Feb 4, 2026Updated 3 weeks ago
- A universal ML model to predict molecular dynamics trajectories with long time steps☆36Updated this week
- AbBFN2: A flexible antibody foundation model based on Bayesian Flow Networks☆37Jun 4, 2025Updated 8 months ago
- Heat-conductivity benchmark test for foundational machine-learning potentials☆30Jan 29, 2026Updated last month
- Local Environment-based Atomic Features☆13Dec 19, 2024Updated last year
- Universal interatomic potentials for advanced materials modeling☆146Updated this week
- A collection of simulation recipes for the atomic-scale modeling of materials and molecules☆35Updated this week
- 🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics …☆90Updated this week
- DiffSyn: A Generative Diffusion Approach to Materials Synthesis Planning (Nature Computational Science, 2026)☆28Feb 10, 2026Updated 2 weeks ago
- Benchmarking foundation Machine Learning Potentials with Lattice Thermal Conductivity from Anharmonic Phonons☆16Oct 30, 2024Updated last year
- Quick Uncertainty and Entropy via STructural Similarity☆56Updated this week
- Collection of tutorials to use the MACE machine learning force field.☆53Jan 22, 2026Updated last month
- Alchemical machine learning interatomic potentials☆34Nov 8, 2024Updated last year
- Some tutorial-style examples for validating machine-learned interatomic potentials☆34Dec 4, 2023Updated 2 years ago
- Zero Shot Molecular Generation via Similarity Kernels☆28Aug 27, 2025Updated 6 months ago
- Torch-native, batchable, atomistic simulations.☆421Updated this week
- Atomistic machine learning models you can use everywhere for everything☆34Updated this week
- This is the repository of code and data for paper "Machine learning-enabled chemical space exploration of all-inorganic perovskites for p…☆10Sep 23, 2024Updated last year