Tobin Isaac

Robust expected information gain for optimal Bayesian experimental design using ambiguity sets

The ranking of experiments by expected information gain (EIG) in Bayesian experimental design is sensitive to changes in the model’s prior distribution, and the approximation of EIG yielded by sampling will have errors similar to the use of a perturbed prior. We define and analyze Robust Expected In…