2 papers
stat.ME2026
Surrogate-Based Bayesian Inference: Uncertainty Quantification and Active Learning
Andrew Gerard Roberts, Michael C. Dietze, Jonathan H. Huggins
Surrogate models - also called emulators - are widely used to facilitate Bayesian inference in settings where computational costs preclude the use of standard posterior inference a…
stat.ME2026
Propagating Surrogate Uncertainty in Bayesian Inverse Problems
Andrew Gerard Roberts, Michael Dietze, Jonathan H. Huggins
Standard Bayesian inference schemes are infeasible for inverse problems with computationally expensive forward models. A common solution is to replace the model with a cheaper surr…