Course: CAAM 31150=STAT 31150
Title: Inverse Problems and Data Assimilation
Instructor(s): Daniel Sanz-Alonso
Teaching Assistant(s): TBA
Class Schedule: Sec 1: TR 2:00 PM–3:20 PM
Location: Harper 130
Description: This class provides an introduction to Bayesian Inverse Problems and Data Assimilation, emphasizing the theoretical and algorithmic inter-relations between both subjects. We will study Gaussian approximations and optimization and sampling algorithms, including a variety of Kalman-based and particle filters as well as Markov chain Monte Carlo schemes designed for high-dimensional inverse problems.