GAMM AG Workshop Computational and Mathematical Methods in Data Science

Program

 
Thursday, September 10, 2020
09:30 - 10:15   Marco Cuturi (Google Brain & Institut Polytechnique de Paris)
Supervised Quantile Normalization for Matrix Factorization using Optimal Transport
abstract
10:15 - 10:45   Break
10:45 - 11:15   Kathlén Kohn (KTH Stockholm)
Invariant theory and scaling algorithms for maximum likelihood estimation
abstract
11:15 - 11:45   Axel Klawonn (University of Cologne)
Machine learning in adaptive domain decomposition methods
abstract
11:45 - 12:15   Guido Montúfar (Max Planck Institute for Mathematics in the Sciences)
Computing the Unique Information
abstract
12:15 - 14:00   Break
14:00 - 14:45   Ivan Oseledets (Skoltech Moscow)
Robustness of deep neural network models
 
14:45 - 15:15   Break
15:15 - 15:45   Ekaterina Muravleva (Skoltech Moscow)
Generative adversarial networks and their application to microstructure synthesis
 
15:45 - 16:15   Daniel Kressner (EPF Lausanne)
Randomized trace estimates for indefinite matrices with an application to determinants abstract
16:15 - 17:30   Break
17:30 - 18:15   Joel Tropp (California Institute of Technology)
SketchySVD abstract
 
Friday, September 11, 2020
09:30 - 10:15   Gitta Kutyniok (TU Berlin)
The Mathematics of Deep Learning: Can we Open the Black Box of Deep Neural Networks? abstract
10:15 - 10:45   Break
10:45 - 11:15   Ingo Steinwart (University of Stuttgart)
Density-Based Cluster Analysis abstract
11:15 - 11:45   Christoph Schnörr (Heidelberg University)
Assignment Flows for Data Labeling and Pattern Formation on Graphs abstract

 

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
26.04.2021, 11:36