Workshop on Optimal Transport
from Theory to Applications
Interfacing Dynamical Systems, Optimization, and Machine Learning
Venue: Humboldt University of Berlin, Dorotheenstraße 24
Berlin, Germany. March 11th - 15th, 2024
Optimal transport (OT) is a theory connecting PDEs, geometry, and probability theory. Recent developments in numerical algorithms for OT problems have further opened new applications, e.g., in statistics, machine learning, imaging, and optimization.
The OT-DOM workshop brings together international experts in OT theory as well as domain experts in applied areas, such as machine learning, optimization, and engineering, to gather in Berlin, Germany. The workshop book is available here. We have made the talk slides available here.
Invited Speakers
Leatitia Chapel (U de Bretagne, France)
Julie Delon (U Paris Cité, France)
Virginie Ehrlacher (ENPC, France)
Guillaume Carlier (U Paris Dauphine, France)
Emtiyaz Khan (RIKEN, Japan)
Anna Korba (ENSAE/CREST Paris, France)
Daniel Kuhn (EPFL, Switzerland)
Wuchen Li (University of South Carolina, USA)
Xue-Mei Li (EPFL, Switzerland)
Alexander Mielke (WIAS, Berlin, Germany)
Olga Mula (TU Eindhoven, The Netherlands)
Jan Maas (IST Austria, Austria)
Hongseok Namkoong (Columbia University, USA)
Tim Laux (University of Regensburg, Germany)
Mijung Park (TU Denmark, Denmark)
Mark Peletier (TU Eindhoven, The Netherlands)
Gabriel Peyré (École Normale Supérieure, France)
Massimiliano Pontil (IIT, Italy & UCL, UK)
Philippe Rigollet (MIT, USA)
Taiji Suzuki (University of Tokyo, Japan)
Bernhard Schmitzer (U Göttingen, Germany)
Jiaxin Shi (Google DeepMind, UK)
Claudia Totzeck (U Wuppertal, Germany)
Oliver Tse (TU Eindhoven, The Netherlands)
Chaoyue Zhao (U Washington, USA)
Organizers
Scientific advisory committee
Alexander Mielke
Vladimir Spokoiny
Peter Friz
Local organizing Team
Christine Schneider
Andrea Eismann