#deep-learning
BMS Summer School on Mathematics of Deep Learning
This summer the Berlin Mathematical School will be offering the BMS Summer School 2019 on “Mathematics of Deep Learning”, 19–30 August 2019, at the Zuse Institute Berlin.
This summer school is aimed at graduate students in mathematics; postdocs are also encouraged to attend. It will offer lectures on both the theory of deep neural networks, and related questions such as generalization, expressivity, or explainability, as well as on applications of deep neural networks (e.g. to PDEs, inverse problems, or specific real-world problems).
The first week will be devoted to the theory of deep neural networks, while the second week has a focus on applications. The format is dominated by 1.5-hour lectures by international experts. In addition, there will also be a poster session for the participants.
Speakers include: Taco Cohen (Qualcomm), Francois Fleuret (IDIAP | EPF, Lausanne), Eldad Haber (University of British Columbia), Robert Jenssen (Tromso), Andreas Krause (ETH Zurich), Gitta Kutyniok (TU Berlin), Ben Leimkuhler (U Edinburgh), Klaus-Robert Müller (TU Berlin), Frank Noe (FU Berlin), Christof Schütte (FU Berlin | ZIB), Vladimir Spokoiny (HU Berlin | WIAS), Rene Vidal (Johns Hopkins University).
For more information, see www.mathplus.de and www.math-berlin.de/academics/summer-schools. The deadline for application is 8 April 2019.
Published on Sunday 24 March 2019 at 08:00 UTC #event #bms #deep-learning