25 citations · 66 across the 16 of their papers we have counts for
3 papers · 1 filter
An approach for finding fully Bayesian optimal designs using normal-based approximations to loss functions
Antony M. Overstall, James M. McGree, Christopher C. Drovandi
The generation of decision-theoretic Bayesian optimal designs is complicated by the significant computational challenge of minimising an analytically intractable expected loss func…
Bayesian design of experiments for generalised linear models and dimensional analysis with industrial and scientific application
David C. Woods, Antony M. Overstall, Maria Adamou +1
The design of an experiment can be always be considered at least implicitly Bayesian, with prior knowledge used informally to aid decisions such as the variables to be studied and…
Bayesian prediction for physical models with application to the optimization of the synthesis of pharmaceutical products using chemical kinetics
Antony Overstall, David Woods, Kieran Martin
Quality control in industrial processes is increasingly making use of prior scientific knowledge, often encoded in physical models that require numerical approximation. Statistical…