EU Regional School - Stuart Seminar
Prof. Stuart - Uncertainty Quantification in Statistical Inverse Problems
Many problems in the physical sciences require the determination of an unknown set of parameters, or field, from a finite set of indirect and noisy measurements. Examples are numerous and include oceanography, oil recovery, water resource management and weather forecasting. The Bayesian approach to these problems is a natural way to provide estimates of the unknown parameters or field, together with a quantification of the uncertainty associated with the estimate. In this talk I will describe an emerging mathematical and algorithmic framework for these problems, explaining the resulting well-posedness and stability theory, and showing how it leads to novel computational algorithms.
For an extended abstract, and references to the wider literature, please see: