Bayesian inverse problems in function spaces: Theory and computation

Prof. Dr. Tim Sullivan (Freie Universität Berlin and Zuse Institute Berlin)

Abstract

Inverse problems, meaning the reconstruction of parameters or dynamically changing states in a mathematical model, which should best explain some given observational data, are ubiquitous in applied sciences. This course provides an introduction to the Bayesian approach to inverse problems, with particular attention to inverse problems in infinite-dimensional spaces, i.e. inverse problems in which we wish to recover a function or field. The infinite-dimensional viewpoint delivers both a mathematically satisfying theory and powerful computational algorithms for problems with large finite dimension.

1. Examples of inverse problems in mathematics and the physical sciences
2. Preliminaries from linear functional analysis
3. Preliminaries from probability theory
4. Bayesian inverse problems in infinite-dimensional problems
5. Monte Carlo and other methods for Bayesian inverse problems

Registration

No registration required.

Date and Place

All sessions take place in Room 02.06.011, Zentrum Mathematik, TUM, Garching Forschungszentrum

• Monday, 23.09.2019:
  • 10:15 - 11:45 and 15:00 - 15:45

• Tuesday, 24.09.2019:
  • 10:15 - 11:45 and 15:00 - 15:45

• Wednesday, 25.09.2019:
  • 10:15 - 11:45 and 15:00 - 15:45

• Thursday, 26.09.2019:
  • 10:15 - 11:45 and 15:00 - 15:45

• Friday, 27.09.2019:
  • 10:15 - 11:45 and 15:00 - 15:45

All participants receive a confirmation certificate for 12 credit hours.

-- DianeClaytonWinter - 10 Jul 2019