ai4materials allows to perform complex analysis of materials science data, using machine learning and compressed sensing techniques. It also provide functions to pre-process (on parallel processors), save and subsequently load materials science datasets, thus easing the traceability, reproducibility, and prototyping of new models.
On the left panel, you can find a few examples that showcase what ai4materials can do.
Extensive documentation can be found here: https://ai4materials.readthedocs.io/en/latest/
Code author: Angelo Ziletti, Ph.D. (angelo.ziletti@gmail.com; ziletti@fhi-berlin.mpg.de)