Likelihood-free Bayesian estimation of multivariate quantile distributions. - Christopher C. Drovandi; Anthony N. Pettitt (Comput. Stat. Data Anal., 2011)

Sequential Monte Carlo for Bayesian sequentially designed experiments for discrete data. - Christopher C. Drovandi; James M. McGree; Anthony N. Pettitt (Comput. Stat. Data Anal., 2013)

Marginal reversible jump Markov chain Monte Carlo with application to motor unit number estimation. - Christopher C. Drovandi; Anthony N. Pettitt; Robert D. Henderson; Pamela A. McCombe (Comput. Stat. Data Anal., 2014)

Towards Bayesian experimental design for nonlinear models that require a large number of sampling times. - Elizabeth G. Ryan; Christopher C. Drovandi; M. Helen Thompson; Anthony N. Pettitt (Comput. Stat. Data Anal., 2014)

Simulation-based fully Bayesian experimental design for mixed effects models. - Elizabeth G. Ryan; Christopher C. Drovandi; Anthony N. Pettitt (Comput. Stat. Data Anal., 2015)

Fully Bayesian Experimental Design for Pharmacokinetic Studies. - Elizabeth G. Ryan; Christopher C. Drovandi; Anthony N. Pettitt (Entropy, 2015)

Melanoma Cell Colony Expansion Parameters Revealed by Approximate Bayesian Computation. - Brenda N. Vo; Christopher C. Drovandi; Anthony N. Pettitt; Graeme J. Pettet (PLoS Comput. Biol., 2015)

Pre-processing for approximate Bayesian computation in image analysis. - Matthew T. Moores; Christopher C. Drovandi; Kerrie L. Mengersen; Christian P. Robert (Stat. Comput., 2015)

A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design. - James M. McGree; Christopher C. Drovandi; Gentry White; Anthony N. Pettitt (Stat. Comput., 2016)

Dimension Reduction for the Emulation of Cardiac Electrophysiology Models for Single Cells and Tissue. - Brodie Lawson; Chris Drovandi; Pamela M. Burrage; Blanca Rodríguez; Kevin Burrage (CinC, 2017)

The talking book: participatory design of an icon-based user interface for rural people with low literacy. - Andrew Bayor; Clifford Schmidt; Fidelis Dauri; Noel Wilson; Christopher C. Drovandi; Margot Brereton (AfriCHI, 2018)

Optimal Bayesian design for discriminating between models with intractable likelihoods in epidemiology. - Mahasen B. Dehideniya; Christopher C. Drovandi; James M. McGree (Comput. Stat. Data Anal., 2018)

Accelerating pseudo-marginal MCMC using Gaussian processes. - Christopher C. Drovandi; Matthew T. Moores; Richard J. Boys (Comput. Stat. Data Anal., 2018)

ABC model selection for spatial extremes models applied to South Australian maximum temperature data. - Xing Ju Lee; Markus Hainy; James P. McKeone; Christopher C. Drovandi; Anthony N. Pettitt (Comput. Stat. Data Anal., 2018)

Likelihood-free inference in high dimensions with synthetic likelihood. - Victor M. H. Ong; David J. Nott; Minh-Ngoc Tran; Scott A. Sisson; Christopher C. Drovandi (Comput. Stat. Data Anal., 2018)

Variational Bayes with synthetic likelihood. - Victor M. H. Ong; David J. Nott; Minh-Ngoc Tran; Scott A. Sisson; Christopher C. Drovandi (Stat. Comput., 2018)

An approach for finding fully Bayesian optimal designs using normal-based approximations to loss functions. - Antony M. Overstall; James M. McGree; Christopher C. Drovandi (Stat. Comput., 2018)

Using History Matching for Prior Choice. - Xueou Wang; David J. Nott; Christopher C. Drovandi; Kerrie L. Mengersen; Michael Evans (Technometrics, 2018)

Acceleration of expensive computations in Bayesian statistics using vector operations. - David J. Warne; Scott A. Sisson; Christopher C. Drovandi (CoRR, 2019)

Sequential Bayesian Experimental Design for Implicit Models via Mutual Information. - Steven Kleinegesse; Christopher C. Drovandi; Michael U. Gutmann (CoRR, 2020)

Estimating a novel stochastic model for within-field disease dynamics of banana bunchy top virus via approximate Bayesian computation. - Abhishek Varghese; Christopher C. Drovandi; Antonietta Mira; Kerrie L. Mengersen (PLoS Comput. Biol., 2020)

Robust Bayesian synthetic likelihood via a semi-parametric approach. - Ziwen An; David J. Nott; Christopher C. Drovandi (Stat. Comput., 2020)

A Laplace-based algorithm for Bayesian adaptive design. - S. G. J. Senarathne; Christopher C. Drovandi; James M. McGree (Stat. Comput., 2020)

Inference of Ventricular Activation Properties from Twelve-lead Electrocardiogram. - Julià Camps; Brodie Lawson; Christopher C. Drovandi; Ana Mincholé; Zhinuo J. Wang; Vicente Grau; Kevin Burrage; Blanca Rodríguez (CinC, 2021)

Advanced Bayesian approaches for state-space models with a case study on soil carbon sequestration. - Mohammad-Javad Davoudabadi; Daniel Edward Pagendam; Christopher C. Drovandi; Jeff Baldock; Gentry White (Environ. Model. Softw., 2021)

Robust Approximate Bayesian Inference With Synthetic Likelihood. - David T. Frazier; Christopher C. Drovandi (J. Comput. Graph. Stat., 2021)

A Semiautomatic Method for History Matching Using Sequential Monte Carlo. - Christopher C. Drovandi; David J. Nott; Daniel Edward Pagendam (SIAM/ASA J. Uncertain. Quantification, 2021)

Inference of ventricular activation properties from non-invasive electrocardiography. - Julià Camps; Brodie Lawson; Christopher C. Drovandi; Ana Mincholé; Zhinuo J. Wang; Vicente Grau; Kevin Burrage; Blanca Rodríguez (Medical Image Anal., 2021)

Accelerating sequential Monte Carlo with surrogate likelihoods. - Joshua J. Bon; Anthony Lee; Christopher C. Drovandi (Stat. Comput., 2021)

Efficient Bayesian Synthetic Likelihood With Whitening Transformations. - Jacob W. Priddle; Scott A. Sisson; David T. Frazier; Ian W. Turner; Christopher C. Drovandi (J. Comput. Graph. Stat., 2022)

BSL: An R Package for Efficient Parameter Estimation for Simulation-Based Models via Bayesian Synthetic Likelihood. - Ziwen An; Leah F. South; Christopher C. Drovandi (J. Stat. Softw., 2022)

A comparison of likelihood-free methods with and without summary statistics. - Christopher C. Drovandi; David T. Frazier (Stat. Comput., 2022)

Optimal Bayesian design for model discrimination via classification. - Markus Hainy; David J. Price; Olivier Restif; Christopher C. Drovandi (Stat. Comput., 2022)

Efficient inference and identifiability analysis for differential equation models with random parameters. - Alexander P. Browning; Christopher C. Drovandi; Ian W. Turner; Adrianne L. Jenner; Matthew J. Simpson (PLoS Comput. Biol., 2022)

Computationally efficient mechanism discovery for cell invasion with uncertainty quantification. - Daniel J. Vandenheuvel; Christopher C. Drovandi; Matthew J. Simpson (PLoS Comput. Biol., 2022)

Transport Reversible Jump Proposals. - Laurence Davies; Robert Salomone; Matthew Sutton; Chris Drovandi (AISTATS, 2023)

Misspecification-robust Sequential Neural Likelihood. - Ryan P. Kelly; David J. Nott; David T. Frazier; David J. Warne; Chris Drovandi (CoRR, 2023)

Strategic model reduction by analysing model sloppiness: A case study in coral calcification. - Sarah A. Vollert; Christopher C. Drovandi; Gloria M. Monsalve-Bravo; Matthew P. Adams (Environ. Model. Softw., 2023)

Modularized Bayesian analyses and cutting feedback in likelihood-free inference. - Atlanta Chakraborty; David J. Nott; Christopher C. Drovandi; David T. Frazier; Scott A. Sisson (Stat. Comput., 2023)

Automatically adapting the number of state particles in SMC2. - Imke Botha; Robert Kohn; Leah F. South; Christopher C. Drovandi (Stat. Comput., 2023)

The effect of biologically mediated decay rates on modelling soil carbon sequestration in agricultural settings. - Mohammad-Javad Davoudabadi; Daniel Edward Pagendam; Christopher C. Drovandi; Jeff Baldock; Gentry White (Environ. Model. Softw., 2023)

Transformations in semi-parametric Bayesian synthetic likelihood. - Jacob W. Priddle; Christopher C. Drovandi (Comput. Stat. Data Anal., 2023)

The Statistical Accuracy of Neural Posterior and Likelihood Estimation. - David T. Frazier; Ryan P. Kelly; Christopher C. Drovandi; David J. Warne (CoRR, 2024)

The Polynomial Stein Discrepancy for Assessing Moment Convergence. - Narayan Srinivasan; Matthew Sutton; Christopher C. Drovandi; Leah F. South (CoRR, 2024)

Improving the Accuracy of Marginal Approximations in Likelihood-Free Inference via Localization. - Christopher C. Drovandi; David J. Nott; David T. Frazier (J. Comput. Graph. Stat., 2024)

Perlin noise generation of physiologically realistic cardiac fibrosis. - Brodie A. J. Lawson; Christopher C. Drovandi; Pamela M. Burrage; Alfonso Bueno-Orovio; Rodrigo Weber dos Santos; Blanca Rodríguez; Kerrie L. Mengersen; Kevin Burrage (Medical Image Anal., 2024)

Unlocking ensemble ecosystem modelling for large and complex networks. - Sarah A. Vollert; Christopher C. Drovandi; Matthew P. Adams (PLoS Comput. Biol., 2024)

Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference. - Ryan P. Kelly; David J. Nott; David T. Frazier; David J. Warne; Christopher C. Drovandi (Trans. Mach. Learn. Res., 2024)

Preconditioned Neural Posterior Estimation for Likelihood-free Inference. - Xiaoyu Wang; Ryan P. Kelly; David J. Warne; Christopher C. Drovandi (Trans. Mach. Learn. Res., 2024)

Generalised likelihood profiles for models with intractable likelihoods. - David J. Warne; Oliver J. Maclaren; Elliot J. Carr; Matthew J. Simpson; Christopher C. Drovandi (Stat. Comput., 2024)

LooplessFluxSampler: an efficient toolbox for sampling the loopless flux solution space of metabolic models. - Pedro A. Saa; Sebastian Zapararte; Christopher C. Drovandi; Lars Keld Nielsen (BMC Bioinform., 2024)

Simulation-based Bayesian inference under model misspecification. - Ryan P. Kelly; David J. Warne; David T. Frazier; David J. Nott; Michael U. Gutmann; Christopher C. Drovandi (CoRR, 2025)