JULAIN-Journal-Club.md

@@ -18,28 +18,10 @@ If you’re interested in more details about the Journal Club, please subscribe
 
 ## Next Meeting
 
-### ! moved! 22 February 2021 Explainable Machine Learning
+### 15 March 2021 Model uncertainty
 
 Virtual Meeting using [BigBlueButton](https://webconf.fz-juelich.de/b/wen-mym-pj7)
  
-* 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>
-https://doi.org/10.1038/s41467-019-08987-4<br>
-6 pages 
-
-* Discovering physical concepts with neural networks<br>
-Raban Iten, Tony Metger, Henrik Wilming, Lidia del Rio, Renato Renner <br>
-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>
 Alex Kendall, Yarin Gal<br>
 NIPS2017<br>
@@ -54,6 +36,8 @@ https://arxiv.org/abs/1505.05424<br>
 
 Intro by Clara Betancourt (JSC)
 
+## Schedule for upcoming Meetings
+
 ### 19 April 2021 Model uncertainty
 * A Simple Baseline for Bayesian Uncertainty in Deep Learning<br>
 Wesley J. Maddox, Timur Garipov, Pavel Izmailov, Dmitry Vetrov, Andrew Gordon Wilson<br>
@@ -68,6 +52,30 @@ https://arxiv.org/pdf/1907.06890.pdf
 
 ## Past Meetings
 
+### 22 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>
+https://doi.org/10.1038/s41467-019-08987-4<br>
+6 pages 
+
+* Discovering physical concepts with neural networks<br>
+Raban Iten, Tony Metger, Henrik Wilming, Lidia del Rio, Renato Renner <br>
+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)
+
+* slides tbd
+* from the meeting:
+   * reminder to register for the Juelich Challenges Hackathon [[here](https://hifis-events.hzdr.de/event/51/)]
+   * follow up paper worth reading: <br>
+Lundberg et al 2020, __From local explanations to global understanding with explainable AI for trees__, Nature Machine Intelligence 2, pages56–67(2020) 
+[link](https://www.nature.com/articles/s42256-019-0138-9)
+
+
 ### 18 January 2021 Explainable Machine Learning
 
 * Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems<br>
@@ -253,4 +261,4 @@ A training schedule using filter pruning and orthogonal reinitialization
 
 
 ---
-last change: 17.2.2021 sw
+last change: 22.2.2021 sw