38 citations · 45 across the 3 of their papers we have counts for
3 papers
A synthetic likelihood-based Laplace approximation for efficient design of biological processes
Mahasen Dehideniya, Antony M. Overstall, Chris C. Drovandi +1
Complex models used to describe biological processes in epidemiology and ecology often have computationally intractable or expensive likelihoods. This poses significant challenges…
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…
Pre-processing for approximate Bayesian computation in image analysis
Matthew T. Moores, Christopher C. Drovandi, Kerrie Mengersen +1
Most of the existing algorithms for approximate Bayesian computation (ABC) assume that it is feasible to simulate pseudo-data from the model at each iteration. However, the computa…