Cross-platform Optimizer for ML Interatomic Potentials
☆24Aug 31, 2025Updated 10 months ago
Alternatives and similar repositories for XPOT
Users that are interested in XPOT are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- dataset augmentation for atomistic machine learning☆25Nov 21, 2025Updated 8 months ago
- ⚛ download and manipulate atomistic datasets☆49Nov 25, 2025Updated 7 months ago
- Julia implementation of algorithm for counting primitive rings in an atomistic structure. Useful for materials simulations☆20Nov 28, 2023Updated 2 years ago
- train and use graph-based ML models of potential energy surfaces☆127Jul 13, 2026Updated last week
- Alchemical machine learning interatomic potentials☆36Nov 8, 2024Updated last year
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- ☆16Apr 22, 2025Updated last year
- A 22.9 million carbon atom dataset☆16Mar 7, 2023Updated 3 years ago
- Code for automated fitting of machine learned interatomic potentials.☆152Updated this week
- A collection of files related to machine learning force fields☆25Oct 25, 2023Updated 2 years ago
- This is a repository containing an advanced tutorial for jobflow (https://github.com/materialsproject/jobflow) related to computational …☆17Jun 5, 2023Updated 3 years ago
- Crystal Host-Guided Generation☆19Apr 24, 2025Updated last year
- ☆11Sep 16, 2024Updated last year
- ☆17Jun 9, 2026Updated last month
- Reproduction of CGCNN for predicting material properties☆27Jul 7, 2026Updated 2 weeks ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Computing representations for atomistic machine learning☆82Jun 25, 2026Updated 3 weeks ago
- ☆111Jun 5, 2026Updated last month
- Training Neural Network potentials through customizable routines in JAX.☆73Jun 30, 2026Updated 3 weeks ago
- ☆16Oct 1, 2023Updated 2 years ago
- Collective atomic modulation analysis with irreducible space-group representation☆18Updated this week
- Active Learning for Machine Learning Potentials☆69Jun 20, 2026Updated last month
- Implementation for AtomMOF: All-Atom Flow Matching for MOF-Adsorbate Structure Prediction☆16Feb 15, 2026Updated 5 months ago
- Benchmarking foundation Machine Learning Potentials with Lattice Thermal Conductivity from Anharmonic Phonons☆16Oct 30, 2024Updated last year
- Some tutorial-style examples for validating machine-learned interatomic potentials☆35Dec 4, 2023Updated 2 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- A Benchmarking Framework for Crystal GNNs☆21Jan 3, 2024Updated 2 years ago
- Python Workflow Definition - workflow interoperability for aiida, jobflow and pyiron☆18Jul 2, 2026Updated 2 weeks ago
- An ASE-friendly implementation of the amorphous-to-crystalline (a2c) workflow.☆18Oct 19, 2025Updated 9 months ago
- Local Environment-based Atomic Features☆13Dec 19, 2024Updated last year
- A Python package for estimating diffusion properties from molecular dynamics simulations.☆86Jul 13, 2026Updated last week
- Atomistic machine learning models you can use everywhere for everything☆46Updated this week
- ☆18Feb 26, 2026Updated 4 months ago
- Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIP…☆105Jan 28, 2026Updated 5 months ago
- Enhanced sampling in the representation space of atomistic neural networks.☆15Updated this week
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Pymatgen Core☆21Updated this week
- 🌟 [NeurIPS '25 Spotlight] Fair and transparent benchmark of machine learning interatomic potentials (MLIPs), beyond basic error metrics …☆104Jul 2, 2026Updated 2 weeks ago
- ☆17May 12, 2025Updated last year
- ☆20May 7, 2024Updated 2 years ago
- MLPs fitted using the Latent Ewald Summation (LES) library and associated scripts.☆27May 22, 2026Updated 2 months ago
- Calculate the required k-point density from the input geometry for periodic quantum chemistry calculations☆23Nov 8, 2022Updated 3 years ago
- ☆22May 7, 2025Updated last year