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Speakers

Michael Arbel

Gatsby Computational Neuroscience Unit, University College London

Nihat Ay

Max Planck Institute for Mathematics in the Sciences

Pradeep Banerjee

Max Planck Institute for Mathematics in the Sciences

Eliana Duarte

Max Planck Institute for Mathematics in the Sciences

Yonatan Dukler

UCLA, Department of Mathematics

Asja Fischer

Ruhr-Universität Bochum

Tim Genewein

DeepMind London

Frederik Künstner

École Polytechnique Fédérale de Lausanne

Wuchen Li

UCLA, Department of Mathematics

Luigi Malagò

Romanian Institute of Science and Technology - RIST, Cluj-Napoca

Grégoire Montavon

Machine Learning, Technische Universität Berlin

Razvan Pascanu

DeepMind London

Johannes Rauh

Max Planck Institute for Mathematics in the Sciences

Nico Scherf

Max Planck Institute for Human Cognitive and Brain Sciences

Ingo Steinwart

Universität Stuttgart

Maurice Weiler

Machine Learning Lab, University of Amsterdam

Program

08:30 - 09:00
09:00 - 09:15 Bernd Sturmfels (Max Planck Institute for Mathematics in the Sciences)
09:15 - 09:45 Guido Montúfar (Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany)
09:45 - 10:00
10:00 - 11:00 Nihat Ay (Max Planck Institute for Mathematics in the Sciences)
On the Natural Gradient for Deep Learning
11:00 - 12:00 Tim Genewein (DeepMind London)
Neural Network Compression - model-capacity and parameter redundancy of neural networks
12:00 - 13:00
13:00 - 14:00 Ingo Steinwart (Universität Stuttgart)
A Sober Look at Neural Network Initializations
14:00 - 15:00 Grégoire Montavon (Machine Learning, Technische Universität Berlin)
Explaining the Decisions of Deep Neural Networks
15:00 - 15:30
15:30 - 16:30 Frederik Künstner (École Polytechnique Fédérale de Lausanne)
Limitations of the Empirical Fisher Approximation
16:30 - 18:00
Poster Session & Coffee & Tee
18:00 - 18:30
19:00 - 00:00
09:00 - 10:00
10:00 - 11:00 Razvan Pascanu (DeepMind London)
Looking at data efficiency in RL
11:00 - 12:00 Maurice Weiler (Machine Learning Lab, University of Amsterdam)
Gauge Equivariant Convolutional Networks
12:00 - 13:00
13:00 - 14:00 Johannes Rauh (Max Planck Institute for Mathematics in the Sciences)
Synergy, redundancy and unique information
14:00 - 15:00 Michael Arbel (Gatsby Computational Neuroscience Unit, University College London)
Kernel Distances for Deep Generative Models
15:00 - 16:00
Poster Session & Coffee & Tee
16:00 - 17:00 Yonatan Dukler (UCLA, Department of Mathematics)
Wasserstein of Wasserstein Loss for Learning Generative Models
17:00 - 18:00
Poster Session & Coffee & Tee
19:00 - 00:00
09:00 - 10:00
10:00 - 11:00 Nico Scherf (Max Planck Institute for Human Cognitive and Brain Sciences)
On Open Problems for Deep Learning in Biomedical Image Analysis
11:00 - 12:00 Wuchen Li (UCLA, Department of Mathematics)
Wasserstein Information Geometry
12:00 - 13:00
13:00 - 14:00 Eliana Duarte (Max Planck Institute for Mathematics in the Sciences)
Discrete Statistical Models with Rational Maximum Likelihood Estimator
14:00 - 15:00 Pradeep Banerjee (Max Planck Institute for Mathematics in the Sciences )
The Blackwell Information Bottleneck
15:00 - 15:30
15:30 - 16:30 Luigi Malagò (Romanian Institute of Science and Technology - RIST, Cluj-Napoca)
On the Information Geometry of Word Embeddings
16:30 - 17:00

Participants

Nader Aldoj

Charité - Universitätsmedizin Berlin

Hector Andrade Loarca

Technische Universität Berlin

Michael Arbel

Gatsby Computational Neuroscience Unit, University College London

Nihat Ay

Max Planck Institute for Mathematics in the Sciences

Pradeep Banerjee

Max Planck Institute for Mathematics in the Sciences

Paul Breiding

Max Planck Institute for Mathematics in the Sciences

Felicia Burtscher

Technische Universität Berlin

Goffredo Chirco

Max Planck Institute for Gravitational Physics, Albert Einstein Institute Potsdam

Florio M. Ciaglia

Max Planck Institute for Mathematics in the Sciences

Claus Diem

Universität Leipzig

Eliana Duarte

Max Planck Institute for Mathematics in the Sciences

Yonatan Dukler

UCLA, Department of Mathematics

Christoph Eikemeier

Max Planck Institute for Mathematics in the Sciences

Domenico Felice

Max Planck Institute for Mathematics in the Sciences

Diogo R. Ferreira

IST, University of Lisbon

Asja Fischer

Ruhr-Universität Bochum

Jan Gairing

Ludwig-Maximilians-Universität München

Tim Genewein

DeepMind London

Maximilian Gerwien

University of Applied Sciences, Leipzig

Alex Goeßmann

Technische Universität Berlin

Volker Göhler

TU Bergakademie Freiberg

Christiane Görgen

Max Planck Institute for Mathematics in the Sciences

Paul Görlach

Max Planck Institute for Mathematics in the Sciences

Gaëtan Hadjeres

Sony Computer Science Laboratories, Paris

Petru Hlihor

Romanian Institute of Science and Technology

Danijela Horak

AIG

Andreas Kofler

Charité - Universitätsmedizin Berlin

Pankaj Kumar

Copenhagen Business School

Frederik Künstner

École Polytechnique Fédérale de Lausanne

Christian Lehn

Chemnitz University of Technology

Wuchen Li

UCLA, Department of Mathematics

Luigi Malagò

Romanian Institute of Science and Technology - RIST, Cluj-Napoca

Orlando Marigliano

Max Planck Institute for Mathematics in the Sciences

Jörg Martin

Physikalisch Technische Bundesanstalt

Grégoire Montavon

Machine Learning, Technische Universität Berlin

Guido Montúfar

Max Planck Institute for Mathematics in the Sciences

Johannes Müller

Albert Ludwig University of Freiburg

Dominik Otto

Fraunhofer IZI

Katerina Papagiannouli

Humboldt-Universität zu Berlin

Razvan Pascanu

DeepMind London

Kornelius Podranski

Max Planck Institute for Human Cognitive and Brain Sciences

Johannes Rauh

Max Planck Institute for Mathematics in the Sciences

Yue Ren

Max Planck Institute for Mathematics in the Sciences

Upasana Roy

University of Leipzig

Nico Scherf

Max Planck Institute for Human Cognitive and Brain Sciences

Ekkehard Schnoor

RWTH Aachen

Martin Skrodzki

Freie Universität Berlin

Liam Solus

KTH Royal Institute of Technology

Ingo Steinwart

Universität Stuttgart

Bernd Sturmfels

Max Planck Institute for Mathematics in the Sciences

Omri Tal

Max Planck Institute for Mathematics in the Sciences

Konstantin Thierbach

Max Planck Institute for Human Cognitive and Brain Sciences

Tat Dat Tran

Max Planck Institute for Mathematics in the Sciences

Csongor-Huba Varady

Romanian Institute of Science and Technology

Nathaniel Virgo

Earth-Life Science Institute (ELSI), Tokyo

Julien Vitay

Technische Universität Chemnitz

Christian Wald

Charité - Universitätsmedizin Berlin

Maurice Weiler

Machine Learning Lab, University of Amsterdam

Felix Weiske

University of Applied Sciences, Leipzig

Scientific Organizers

Guido Montúfar

Max Planck Institute for Mathematics in the Sciences

Administrative Contact

Valeria Hünniger

Max-Planck-Institut für Mathematik in den Naturwissenschaften Contact via Mail