

GAMM AG Workshop Computational and Mathematical Methods in Data Science
Speakers
Plenary speakers
- Marco Cuturi (Google Brain & Institut Polytechnique de Paris)
Talk: Supervised Quantile Normalization for Matrix Factorization using Optimal Transport - Gitta Kutyniok (TU Berlin)
Talk: The Mathematics of Deep Learning: Can we Open the Black Box of Deep Neural Networks? - Ivan Oseledets (Skoltech Moscow)
Talk: Robustness of deep neural network models - Joel Tropp (California Institute of Technology)
Talk: SketchySVD
Invited speakers
- Martin Bogdan (Leipzig University)
- Axel Klawonn (University of Cologne)
Talk: Machine learning in adaptive domain decomposition methods - Kathlén Kohn (KTH Stockholm)
Talk: Invariant theory and scaling algorithms for maximum likelihood estimation - Daniel Kressner (EPF Lausanne)
Talk: Randomized trace estimates for indefinite matrices with an application to determinants - Guido Montúfar (Max Planck Institute for Mathematics in the Sciences)
Talk: Computing the Unique Information - Ekaterina Muravleva (Skoltech Moscow)
Talk: Generative adversarial networks and their application to microstructure synthesis - Christoph Schnörr (Heidelberg University)
Talk: Assignment Flows for Data Labeling and Pattern Formation on Graphs - Ingo Steinwart (University of Stuttgart)
Talk: Density-Based Cluster Analysis
Date and Location
September 10 - 11, 2020
Max Planck Institute for Mathematics in the Sciences
Virtual event - Videobroadcast
Scientific Organizers
Max von Renesse
Leipzig University
André Uschmajew
MPI for Mathematics in the Sciences
Administrative Contact
Valeria HünnigerMPI for Mathematics in the Sciences
Contact by Email