From 873dd8f5f15ebe84af9c343e9cebc87a7db4e055 Mon Sep 17 00:00:00 2001
From: Luigi Sbailo <sbailo@fhi-berlin.mpg.de>
Date: Wed, 24 Mar 2021 10:28:23 +0100
Subject: [PATCH] Update tutorials.json
---
tutorials.json | 41 ++++++++++++++++++++++++++++++++++++++++-
1 file changed, 40 insertions(+), 1 deletion(-)
diff --git a/tutorials.json b/tutorials.json
index c43c2c04..6150b8a3 100644
--- a/tutorials.json
+++ b/tutorials.json
@@ -747,7 +747,7 @@
"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 will give an introduction to ARISE (Leitherer, Ziletti, Ghiringhelli arXiv:2103.09777).",
- "url": "https://gitlab.mpcdf.mpg.de/nomad-lab/analytics-tutorial-template",
+ "url": "https://gitlab.mpcdf.mpg.de/nomad-lab/analytics-arise",
"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",
"link_paper": "https://arxiv.org/abs/2103.09777",
@@ -784,6 +784,45 @@
"jupyter"
]
}
+ },
+ {
+ "authors": [
+ "Leitherer, Andreas",
+ "Sbailò, Luigi",
+ "Ghiringhelli, Luca M."
+ ],
+ "email": "leitherer@fhi-berlin.mpg.de",
+ "title": "Hands-on tutorial: Regression using multilayer perceptrons",
+ "description": "In this tutorial we will use the ElemNet neural network architecture (https://github.com/NU-CUCIS/ElemNet) to predict the volume per atom of inorganic compounds, where the open quantum materials database (OQMD) is used as a resource (specifically, the data is taken from Ward et. al., npj Comput. Mater. 2, 16028 (2016)).",
+ "url": "https://gitlab.mpcdf.mpg.de/nomad-lab/analytics-nn-regression",
+ "link": "https://analytics-toolkit.nomad-coe.eu/hub/user-redirect/notebooks/tutorials/nn_regression.ipynb",
+ "link_public": "https://analytics-toolkit.nomad-coe.eu/public/user-redirect/notebooks/tutorials/nn_regression.ipynb",
+ "updated": "2020-04-09",
+ "flags":{
+ "featured": true,
+ "top_of_list": false
+ },
+ "labels": {
+ "application_keyword": [
+ "Dee neural networks",
+ "Descriptors"
+ ],
+ "application_section": [
+ "Materials property prediction"
+ ],
+ "application_system": [
+ "Inorganic compounds taken from the OQMD database"
+ ],
+ "category": [
+ "Tutorial"
+ ],
+ "data_analytics_method": [
+ "Neural networks"
+ ],
+ "platform": [
+ "jupyter"
+ ]
+ }
}
]
}
--
GitLab