Previous Events

Mar 19, 2021 Stefanie Jegelka (Machine Learning Group at MIT, USA)
Representation and Learning in Graph Neural Networks
Nov 4, 2020 Stefan Hollands (Leipzig University)
(In)determinism Inside Black Holes
Oct 6, 2020 Constantino Tsallis (Centro Brasileiro de Pesquisas Fisicas, Brazil)
Modern statistical mechanics – Approaching complexity in natural, artificial and social sciences
Aug 4, 2020 Marco Mondelli (IST Austria)
Understanding Gradient Descent for Over-parameterized Deep Neural Networks
Jul 20, 2020 Franca Hoffmann (California Institute of Technology)
Kalman-Wasserstein Gradient Flows
May 14, 2020 Lior Pachter (California Institute of Technology)
Dec 10, 2019 Mikhail Belkin (The Ohio State University, USA)
Nov 14, 2019 Kathlén Kohn (KTH Royal Institute of Technology, Stockholm)
The geometry of neural networks
Oct 23, 2019 Věra Kůrková (Institute of Computer Science, Czech Academy of Sciences, Czech Republic)
Lower Bounds on Complexity of Shallow Networks
Sep 18, 2019 Vladimir Temlyakov (University of South Carolina)
Supervised learning and sampling error of integral norms in function classes
Jul 16, 2019 Lamiae Azizi (The University of Sydney)
A Mathematical trip into the Data Science realm
May 28, 2019 Nicolas Garcia Trillos (Department of Statistics, University of Wisconsin-Madison, USA)
The use of geometry to learn from data, and the learning of geometry from data.
Apr 10, 2019 Gabriel Peyré (CNRS and Ecole Normale Supérieure, Paris, France)
Computational Optimal Transport for Data Sciences
Mar 7, 2019 Stefania Petra (Universität Heidelberg)
Compressed Sensing - From Theory To Practice
Feb 14, 2019 Felix Krahmer (Technische Universität München)
Blind deconvolution with randomness - convex geometry and algorithmic approaches
Jan 28, 2019 Nils Bertschinger (Frankfurt Institute for Advanced Studies - FIAS, Germany)
A geometric structure underlying stock correlations
Nov 8, 2018 Benjamin Fehrmann (University of Oxford)
Convergence rates for mean field stochastic gradient descent algorithms
Sep 27, 2018 Max von Renesse (Universität Leipzig)
Topics in Deterministic and Stochastic Dynamical Systems on Wasserstein Space
Aug 14, 2018 Afonso Bandeira (Courant Institute of Mathematical Sciences, New York)
Statistical estimation under group actions: The Sample Complexity of Multi-Reference Alignment
Jul 11, 2018 Harald Oberhauser (University of Oxford)
Learning laws of stochastic processes
Jun 18, 2018 Anna Seigal (University of California, Berkeley)
Structured Tensors and the Geometry of Data
May 2, 2018 Steffen Lauritzen (University of Copenhagen, Denmark)
Max-linear Bayesian networks
Apr 24, 2018 Benjamin Recht (University of California, Berkeley)
The statistical foundations of learning to control

Administrative Contact

Katharina Matschke

MPI for Mathematics in the Sciences Contact via Mail