GAMM AG Workshop Computational and Mathematical Methods in Data Science


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 Hünniger
MPI for Mathematics in the Sciences
Contact by Email
15.09.2020, 01:27