We are very proud to welcome Gitta Kutyniok from LMU Munich to our lab!
Abstract: One or maybe the main reason for the impressive success of deep neural networks in both public life and science is their amazing generalization ability, namely their performance on unseen data. However, this phenomenon is still to a large extent a mystery.
In this talk, we will provide an introduction to this problem and discuss some recent advances. We will then focus on graph convolutional neural networks and show how to unravel part of the mystery in this situation completely.
Short Bio: Kutyniok was educated in Detmold, and in 1996 earned a diploma in mathematics and computer science at Paderborn University. She completed her doctorate (Dr. rer. nat.) at Paderborn in 2000. Her dissertation, Time-Frequency Analysis on Locally Compact Groups, was supervised by Eberhard Kaniuth.
From 2000 to 2008 she held short-term positions at Paderborn University, the Georgia Institute of Technology, the University of Giessen, Washington University in St. Louis, Princeton University, Stanford University, and Yale University. In 2006 she earned her habilitation in Giessen, in 2008 she became a full professor at Osnabrück University, and in 2011 she was given the Einstein Chair at the Technical University of Berlin. In 2018 she added courtesy affiliations with computer science and electrical engineering at TU Berlin and an adjunct faculty position at the University of Tromsø.. In October 2020 she moved to the Ludwig Maximilian University of Munich, where she holds a Bavarian AI Chair.
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