JULAIN-Journal-Club.md

@@ -18,29 +18,10 @@ If you’re interested in more details about the Journal Club, please subscribe
 
 ## Next Meeting
 
-### 18 January 2021 Explainable Machine Learning
+### 15 February 2021 Explainable Machine Learning
 
 Virtual Meeting using [BigBlueButton](https://webconf.fz-juelich.de/b/wen-mym-pj7)
 
-* Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems<br>
-Laura von Rueden, Sebastian Mayer, Katharina Beckh, Bogdan Georgiev, Sven Giesselbach, Raoul Heese, Birgit Kirsch, Julius Pfrommer, Annika Pick, Rajkumar Ramamurthy, Michal Walczak, Jochen Garcke, Christian Bauckhage, Jannis Schuecker<br>
-Learning, 18, 2019<br>
-https://arxiv.org/pdf/1903.12394.pdf<br>
-16 pages
-
-* Theory-guided Data Science: A New Paradigm for Scientific Discovery from Data<br>
-Anuj Karpatne, Gowtham Atluri, James H. Faghmous, Michael Steinbach, Arindam Banerjee,
-Auroop Ganguly, Shashi Shekhar, Nagiza Samatova, and Vipin Kumar<br>
-IEEE Transactions on Knowledge and Data Engineering, 29(10), 2017, 2318-2331<br>
-https://arxiv.org/pdf/1612.08544.pdf<br>
-12 pages
-
-
-
-## Schedule for upcoming Meetings
-
-### 15 February 2021 Explainable Machine Learning
-
 * Unmasking Clever Hans predictors and assessing what machines really learn<br>
 Sebastian Lapuschkin, Stephan Wäldchen, Alexander Binder, Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller <br>
 Nat Commun 10, 1096 (2019)<br>
@@ -53,6 +34,10 @@ Physical Review Letters, 124(1), 2020, 010508<br>
 https://arxiv.org/abs/1807.10300<br>
 5 pages + 11 pages Appendix :)
 
+Intro by Tobias Tesch (IBG-3)
+
+## Schedule for upcoming Meetings
+
 ### 15 March 2021 Model uncertainty
  
 What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?<br>
@@ -81,6 +66,24 @@ https://arxiv.org/pdf/1907.06890.pdf
 
 ## Past Meetings
 
+### 18 January 2021 Explainable Machine Learning
+
+* Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems<br>
+Laura von Rueden, Sebastian Mayer, Katharina Beckh, Bogdan Georgiev, Sven Giesselbach, Raoul Heese, Birgit Kirsch, Julius Pfrommer, Annika Pick, Rajkumar Ramamurthy, Michal Walczak, Jochen Garcke, Christian Bauckhage, Jannis Schuecker<br>
+Learning, 18, 2019<br>
+https://arxiv.org/pdf/1903.12394.pdf<br>
+16 pages
+
+* Theory-guided Data Science: A New Paradigm for Scientific Discovery from Data<br>
+Anuj Karpatne, Gowtham Atluri, James H. Faghmous, Michael Steinbach, Arindam Banerjee,
+Auroop Ganguly, Shashi Shekhar, Nagiza Samatova, and Vipin Kumar<br>
+IEEE Transactions on Knowledge and Data Engineering, 29(10), 2017, 2318-2331<br>
+https://arxiv.org/pdf/1612.08544.pdf<br>
+12 pages
+
+* Intro by Karim Mache, JSC, Earth System Data Exploration group
+
+
 ### 21 December 2020 Explainable Machine Learning
 
 * Network Dissection: Quantifying Interpretability of Deep Visual Representations<br>