Bernstein Symposium: January 23, 2017

The BCCN Tuebingen has been established on the basis of an 8 Mio Euro project funded by the BMBF to bring together scientists from theoretical and experimental neurobiology, machine learning, and medicine, in order to collaborate on computational neuroscience questions at the interface between neuroscience and machine learning. The BMBF funding was allocated to recruit new research groups, to establish a new Master and PhD program for computational neuroscience, and to pursue collaborative research projects on neural mechanisms of perceptual inference. On the occasion of the upcoming advisory board meeting BCCN group leaders will present at the Bernstein Symposium on January 23rd, showcasing some of the most exciting achievements of the BMBF funding period. We cordially invite everybody interested to attend!

Beyond the BMBF funding period, the BCCN Tübingen will continue its work as an official center of the University of Tuebingen to coordinate collaborative research projects and teaching at the interface between neuroscience and machine learning. The new CRC project on “Robust Vision” funded by the German Science Foundation is a major future focus, and will be the topic of the CRC Kick-Off symposium on January 24th

Confirmed speakers:

Philipp Berens, University of Tübingen, Tübingen, Germany
Peter Gehler, University of Tübingen & Max Planck Institute for Intelligent Systems, Tübingen, Germany
Anna Levina, The Institute of Science and Technology Austria, Klosterburg, Austria
Jakob Macke, research center caesar, Bonn, Germany
Marcel Oberländer, research center caesar, Bonn, Germany
Felix Wichmann, University of Tübingen, Tübingen, Germany

Kick-Off Symposium: January 24, 2017

Starting 2017 the German Science Foundation is going to fund a large collaborative research project (CRC 1233) comprising more than twenty labs that combine neuroscience and machine vision approaches to achieve a better understanding of the principles and algorithms that enable robust visual inference both in biology and machines. The project will build upon the recent breakthrough of deep neural networks in computer vision and focus on areas where the neurobiology of vision prominently diverges from current machine vision algorithms. In particular, the center seeks to make progress on the following three aims:

• the computational use of feedback in the brain and how generative and causal modelling can improve the robustness of visual inference algorithms 
• how robust visual inference is a effected by the dynamics of natural image acquisition

• how robust visual inference is a effected by pre-cortical transformations as determined from neurobiological measurements  

Confirmed speakers:
Dora Angelaki, Baylor College of Medicine, Houston, USA
Thomas Brox, University of Freiburg, Freiburg, Germany

Sanja Fidler, University of Toronto, Canada
Roland Fleming, University of Giessen, Giessen, Germany

Neil Rabinowitz, Google DeepMind, London, UK

Jacob Reimer, Baylor College of Medicine, Houston, USA

Jonathan Victor, Cornell University, New York, USA