From 78eaaef4c44f523e876c92f2e003d0f19b0dd5f7 Mon Sep 17 00:00:00 2001 From: Luigi Sbailo <sbailo@fhi-berlin.mpg.de> Date: Mon, 22 Mar 2021 22:42:02 +0100 Subject: [PATCH] Update tutorials.json --- tutorials.json | 47 +++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 47 insertions(+) diff --git a/tutorials.json b/tutorials.json index ecd62a15..253e52d4 100644 --- a/tutorials.json +++ b/tutorials.json @@ -737,6 +737,53 @@ "jupyter" ] } + }, + { + "authors": [ + "Leitherer, Andreas", + "Ziletti, Angelo", + "Ghiringhelli, Luca M." + ], + "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 will give an introduction to ARISE (Leitherer, Ziletti, Ghiringhelli arXiv:2103.09777).", + "url": "https://gitlab.mpcdf.mpg.de/nomad-lab/analytics-tutorial-template", + "link": "https://analytics-toolkit.nomad-coe.eu/hub/user-redirect/notebooks/tutorials/{tutorial}.ipynb", + "link_public": "https://analytics-toolkit.nomad-coe.eu/public/user-redirect/notebooks/tutorials/{tutorial}.ipynb", + "link_paper": "https://arxiv.org/abs/2103.09777", + "updated": "2021-03-22", + "flags":{ + "featured": true, + "top_of_list": false, + "paper": true + }, + "labels": { + "application_keyword": [ + "Bayesian deep learning", + "Unsupervised learning", + "SOAP", + "grain boundaries", + "binaries", + "ternaries", + "low-dimensional materials" + ], + "application_section": [ + "Timely artificial-intelligence applications to Materials science" + ], + "application_system": [ + "System" + ], + "category": [ + "Tutorial" + ], + "data_analytics_method": [ + "Bayesian deep learning", + "Unsupervised learning" + ], + "platform": [ + "jupyter" + ] + } } ] } -- GitLab