From 2164fe0238bf4193bf5e67279edbf54318703aa6 Mon Sep 17 00:00:00 2001 From: Luigi Sbailo <sbailo@fhi-berlin.mpg.de> Date: Mon, 29 Nov 2021 12:34:21 +0000 Subject: [PATCH] Update metainfo.json --- metainfo.json | 1 + 1 file changed, 1 insertion(+) diff --git a/metainfo.json b/metainfo.json index 67fc93d..49c11e5 100644 --- a/metainfo.json +++ b/metainfo.json @@ -7,6 +7,7 @@ "email": "leitherer@fhi-berlin.mpg.de", "title": "ARISE - Robust recognition and exploratory analysis of crystal structures via Bayesian deep learning", "description": "In this tutorial, we give an introduction to ARISE ((ARtificial-Intelligence-based Structure Evaluation), a powerful Bayesian-deep-neural-network tool for the recognition 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.", + "notebook_name": "ARISE.ipynb", "url": "https://gitlab.mpcdf.mpg.de/nomad-lab/analytics-tutorial-template", "link": "https://analytics-toolkit.nomad-coe.eu/hub/user-redirect/notebooks/tutorials/ARISE.ipynb", "link_public": "https://analytics-toolkit.nomad-coe.eu/public/user-redirect/notebooks/tutorials/ARISE.ipynb", -- GitLab