The workshop on “Mathematics of Deep Learning” will take place on 3-5 December at the WIAS Berlin. It aims to provide a topical view on recent advances regarding mathematical aspects of popular machine learning approaches, in particular (but not limited to) deep learning. While the focus lies on theoretical and conceptual research of network representations, contributions concerned with practical aspects and non-standard methods are also welcome.

The organisers are hosting the following speakers:
* Helmut Bölcskei (ETH Zurich)
* Alexandra Carpentier (Otto von Guericke University Magdeburg)
* Asja Fischer (Ruhr University Bochum)
* Philipp Grohs (University of Vienna)
* Arnulf Jentzen (ETH Zurich)
* Gitta Kutyniok (TU Berlin)
* Anthony Nouy (EC Nantes)
* Ivan Oseledets (Skoltech, Moscow)
* Philipp Petersen (University of Oxford)
* Christoph Schwab (ETH Zurich)
* Ingo Steinwart (University of Stuttgart)
* Miles Stoudenmire (Flatiron Institute, New York)
* Dmitry Yarotsky (Skoltech, Moscow)

For further information and to register please visit the event website: https://www.wias-berlin.de/workshops/DL2019/