Conference Agenda

YRM4: Mathematical theory of deep learning
Monday, 18/Feb/2019:
4:30pm - 6:30pm

Session Chair: Rafael Reisenhofer
Session Chair: Philipp Petersen
Location: HS 41

4:30pm - 4:50pm

Deep convolutional networks from sparse coding principles

J. Sulam1, A. Aberdam2, M. Elad2

1Johns Hopkins University, USA; 2Technion, Israel Institute of Technology, Israel

4:50pm - 5:10pm

Optimal approximation for Wilson bases with ReLU neural networks

D. Perekrestenko

ETH Zurich, Switzerland

5:10pm - 5:30pm

Approximation spaces of deep neural networks

F. Voigtlaender

Catholic University of Eichstätt-Ingolstadt, Germany

5:30pm - 5:50pm

Deep learning for inverse problems. Where are we, and how far can we go?

J. Adler1,2, O. Öktem1

1KTH, Sweden; 2Elekta,Sweden

5:50pm - 6:10pm

Gabor frames and deep scattering networks in audio processing

R. Bammer, M. Dörfler

University of Vienna, Austria

6:10pm - 6:30pm

Invertible neural networks

J. Behrmann

University Bremen, Germany