Termine

Further information

Further information

Further information

Optimal transport has become a central tool for comparing probability measures and extracting representative distributions from heterogeneous data. Yet, in many applications the objects of interest are stochastic processes, and the classical framework ignores a key structural feature: time and information. Indeed, classical Wasserstein barycenters ignore the filtration structure, making them ill-suited for problems in mathematical finance, stochastic control, and sequential decision-making. > > We study Fréchet means with respect to the adapted Wasserstein distance, where transport plans must respect the temporal flow of information. For filtered Gaussian inputs, we establish existence and characterize when the barycenter admits an ordinary Gaussian representative via a rank criterion on a local correlation matrix. We illustrate the difference between adapted and classical barycenters through numerical experiments on autoregressive processes and briefly discuss possible applications in robust stress testing of financial models. > > Based on joint work with Madhu Gunasingam, Johannes Wiesel and Ting-Kam Leonard Wong.

Get an insight into the research of five new postdoctoral researchers of Mathematics Münster. In short scientific presentations they will introduce their topics.
After the talks, there will be the opportunity to exchange ideas while enjoying tea, coffee and cake in the Common Room.

• 1. Adrian Celestino ? Free probability, combinatorics and matrix models
• 2. Arghya Sadhukhan ? From lattices to flags: counting components via representation theory
• 3. Edoardo Tolotti ? Variational homogenization of the nonlinear Stokes problem
• 4. Beatriz Salvador ? From particle systems to PDEs and SPDEs
• 5. Anish Chedalavada ? TBA
• 6. Florian Riedel ? TBA
• 7. Mahdi Haghshenas ? TBA