CUED Publications database

Probabilistic numerical methods for PDE-constrained Bayesian inverse problems

Cockayne, J and Oates, C and Sullivan, T and Girolami, M (2017) Probabilistic numerical methods for PDE-constrained Bayesian inverse problems. In: UNSPECIFIED.

Full text not available from this repository.


This paper develops meshless methods for probabilistically describing discretisation error in the numerical solution of partial differential equations. This construction enables the solution of Bayesian inverse problems while accounting for the impact of the discretisation of the forward problem. In particular, this drives statistical inferences to be more conservative in the presence of significant solver error. Theoretical results are presented describing rates of convergence for the posteriors in both the forward and inverse problems. This method is tested on a challenging inverse problem with a nonlinear forward model.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Depositing User: Cron Job
Date Deposited: 23 Mar 2020 20:02
Last Modified: 13 Apr 2021 09:22
DOI: 10.1063/1.4985359