Statistical Inference for Stochastic PDEs: An Overview (Part I)

Over the course of two or three seminars, we will discuss some recent developments in the area of statistical inference for parabolic stochastic partial differential equations. We will start from some simple inverse type problems from stochastic ordinary differential equations (SDEs) and discuss how some of the methods can be translated to the infinite dimensional case (SPDEs). We will also analyze the key differences between statistical problems for SODEs and SPDEs. Most of the talk will be focused on the so-called spectral approach. Finally, we will investigate the practically important case of discrete sampling of the solution. The talk does not assume prior knowledge of statistical inference for stochastic process, and all relevant results from stochastic analysis will be recalled as needed.

This is an open seminar, and anyone interested in resent advances in the field of Mathematical Finance and Stochastics Analysis are welcome to attend.

Event Topic

Mathematical Finance, Stochastic Analysis, and Machine Learning