An evaluation framework for machine learning models simulating high-throughput materials discovery.
-
Updated
Mar 4, 2026 - Python
An evaluation framework for machine learning models simulating high-throughput materials discovery.
GUI for running simulations with universal machine learning interatomic potentials (MACE, CHGNet, SevenNet, Nequix, ORB, MatterSim, UPET))
The Orchestrator is an integrated software package for building, training, testing, augmenting, running, and analyzing interatomic potentials (IAPs) and their simulations.
Run machine-learning potentials using VASP style inputs.
Add a description, image, and links to the interatomic-potential topic page so that developers can more easily learn about it.
To associate your repository with the interatomic-potential topic, visit your repo's landing page and select "manage topics."