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Graduate seminar SS 19 Graduate Seminar on Numerical Simulation

The approximation theory of deep learning

Offered by
Prof. Michael Griebel
Dr. Bastian Bohn

Content: Probably the most important topic of state-of-the-art mathematical reseach in machine learning is the analysis of complex deep learning models. To this end, the capacity - or approximability - of deep learning model classes is an important indicator for the power of the underlying algorithm. We will discuss recent results on the approximation power of deep ReLU networks and variants thereof, which prove to be a necessary requirement for their success in deep learning.


Each session starts at 14:15 in room 2.035, Endenicher Allee 19b.