MATH 789R - Bayesian Inverse Problems and Uncertainty Quantification


I held this special topics course in the spring of 2016.


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.


The main references for this course are:

Additional material will be assigned as needed.

Lars Ruthotto
Lars Ruthotto
Winship Distinguished Research Associate Professor of Mathematics and Computer Science