For a few decades mathematicians have now been interested in the field of optimal transport, which has manifold applications, e.g.\ in data science, phyics, image processing, or logistics. While it was originally developed for applications, by now it also became a mathematical tool that connects several mathematical disciplines: PDE analysis, optimization, stochastics, numerics, and geometry increasingly use and extend the concept. The basic question is how some amount of material can be transported from (multiple) sources to (multiple) sinks at the lowest possible transport costs. The topic particularly gained importance due to new interpretations of statistical learning or partial differential equations via optimal transport and due to novel algorithms that allow an efficient numerical approximation of optimal transport.
Siehe Learnwebkurs https://www.uni-muenster.de/LearnWeb/learnweb2/course/view.php?id=75260. Die Vorbesprechung soll Ende Januar/Anfang Februar stattfinden (Termin steht noch nicht fest und ist teilweise flexibel, bitte bei Interesse im Learnwebkurs diskutieren).
- Lehrende/r: Johannes Ebert