Neuronale Informationsverarbeitung

Journal Club Summer Term 2018

Day, time & location:

During term time:
Fridays from 11:00 till 12:30 hrs, weekly, starting on April 20th, 2018
72076 Tübingen, Sand 6, room F230

Vorlesungsverzeichnis

Students can obtain 2 ECTS for the active participation in the Journal Club (non graded, only pass or fail). Active participation implies, first, that students have to present at least one paper during term. Second, they have to attend the Journal Club regularly: non-attendance will only be tolerated once per term (unless the student provides a doctor's note).

Finally, the number of participants at the Journal Club is strictly limited to 10, and members of the NIP lab take precedence over external students. Thus in practice there is a limit of 2, 3 or maximally 4 external students per term, depending on the number of current NIP lab members.

Week Date Presenter Paper
1 20.04.2018 Tom Wallis Introduction and paper assignment
2

27.04.2018

Heiko Schütt

Lake, B. M., Ullman, T. D., Tenenbaum, J. B., & Gershman, S. J. (2017). Building machines that learn and think like people. Behavioral and Brain Sciences, 40. [target article]

3

04.05.2018

Tom Wallis

Lake, B. M., Ullman, T. D., Tenenbaum, J. B., & Gershman, S. J. (2017). Building machines that learn and think like people. Behavioral and Brain Sciences, 40. [commentaries + reply]

4

11.05.2018

Malav Shah

Edelman, S., & Shahbazi, R. (2012). Renewing the respect for similarity. Frontiers in Computational Neuroscience, 6. doi.org/10.3389/fncom.2012.00045

5

18.05.2018

no journal club

6

25.05.2018

Pfingsten
7

01.06.2018

Marlene Weller

Ritter, S., Barrett, D. G., Santoro, A., & Botvinick, M. M. (2017). Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study. arXiv Preprint arXiv:1706.08606. Retrieved from arxiv.org/abs/1706.08606

8

08.06.2018

no journal club

9

15.06.2018

Judy Borowski

Zeman, A., Obst, O., Brooks, K. R., & Rich, A. N. (2013). The Müller-Lyer Illusion in a Computational Model of Biological Object Recognition. PLoS ONE, 8(2), e56126. doi.org/10.1371/journal.pone.0056126

10

22.06.2018
-cancelled-

Claudio Michaelis

Spoerer, C. J., McClure, P., & Kriegeskorte, N. (2017). Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition. Frontiers in Psychology, 8. doi.org/10.3389/fpsyg.2017.01551

11 29.06.2018

no journal club

12

06.07.2018

Christina Funke

Watanabe, E., Kitaoka, A., Sakamoto, K., Yasugi, M., & Tanaka, K. (2018). Illusory Motion Reproduced by Deep Neural Networks Trained for Prediction. Frontiers in Psychology, 9. doi.org/10.3389/fpsyg.2018.00345

13

13.07.2018

Felix Wichmann

Fleuret, F., Li, T., Dubout, C., Wampler, E. K., Yantis, S., & Geman, D. (2011). Comparing machines and humans on a visual categorization test. Proceedings of the National Academy of Sciences, 108(43), 17621–17625.

14

20.07.2018

Bernhard Lang

Yan, Z., & Zhou, X. S. (2017). How intelligent are convolutional neural networks? arXiv Preprint arXiv:1709.06126.