Sampling Function Space: Applications and Algorithms
Andrew Stuart (Warwick)

A wide variety of problems arising in applications require the sampling of a probability measure on the space of functions. Examples from econometrics, signal processing, molecular dynamics and data assimilation will be given.

In this situation it is of interest to understand the computational complexity of MCMC methods for sampling the desired probability measure. We overview recent results of this type, highlighting the importance of measures which are absolutely continuous with respect to a Guassian measure.