MATH 789R - Bayesian Inverse Problems and Uncertainty Quantification
Times
I held this special topics course in the spring of 2016.
Description
This special topics course introduces basic concepts as well as more recent advances in Bayesian methods for solving inverse problems. Motivated by real-world applications, we will contrast the frequentists and the Bayesian approach to inverse problems and emphasize the role of regularization/priors. Also, we will explore sampling techniques used for uncertainty quantification. The course introduces relevant theory from discrete probability.
Literature
The main references for this course are:
- An Introduction to Bayesian Scientific Computing by E. Somersalo and D. Calvetti
- Statistical and Computational Inverse Problems by J. Kaipio and E. Somersalo
Additional material will be assigned as needed.
