"title":"ARISE - Robust recognition and exploratory analysis of crystal structures via Bayesian deep learning",
"description":"In this tutorial we will give an introduction to ARISE (Leitherer, Ziletti, Ghiringhelli arXiv:2103.09777).",
"description":"In this tutorial, we give an introduction to ARISE ((ARtificial-Intelligence-based Structure Evaluation), a powerful Bayesian-deep-neural-network tool for therecognition of atomistic structures. ARISE is robust to structural noise and can treat more than 100 crystal structures, a number that can be extended on demand. While being trained on ideal structures only, ARISE correctly characterizes strongly perturbed single- and polycrystalline systems, from both synthetic and experimental resources. The probabilistic nature of the Bayesian-deep-learning model allows to obtain principled uncertainty estimates. By applying unsupervised learning to the internal neural-network representations, one can reveal grain boundaries and (unapparent) structural regions sharing easily interpretable geometrical properties.",
