An Efficient Algorithm for the Detection of Eden. - David J. Warne; Ross F. Hayward; Neil A. Kelson; Dann G. Mallet (Complex Syst., 2013)

Image-based flow visualisation (IBFV) to enhance interpretation of complex flow patterns within a shallow tidal barrier estuary. - David J. Warne; Genevieve Larsen; Joseph Young; Malcolm E. Cox (Environ. Model. Softw., 2013)

Comparison of High Level FPGA Hardware Design for Solving Tri-diagonal Linear Systems. - David J. Warne; Neil A. Kelson; Ross F. Hayward (ICCS, 2014)

The Dynamics of Cellular Automata on 2-Manifolds is Affected by Topology. - David J. Warne; Ross F. Hayward (J. Cell. Autom., 2015)

Multilevel rejection sampling for approximate Bayesian computation. - David J. Warne; Ruth E. Baker; Matthew J. Simpson (Comput. Stat. Data Anal., 2018)

Utility of Genetic Algorithms for Solving Large-Scale Construction Time-Cost Trade-Off Problems. - Duzgun Agdas; David J. Warne; Jorge Osio-Norgaard; Forrest J. Masters (J. Comput. Civ. Eng., 2018)

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

Robust Simulation Design for Generalized Linear Models in Conditions of Heteroscedasticity or Correlation. - Andrew Gill; David J. Warne; Clare McGrory; James M. McGree; Antony M. Overstall (WSC, 2022)

Multifidelity multilevel Monte Carlo to accelerate approximate Bayesian parameter inference for partially observed stochastic processes. - David J. Warne; Thomas P. Prescott; Ruth E. Baker; Matthew J. Simpson (J. Comput. Phys., 2022)

Rapid Bayesian Inference for Expensive Stochastic Models. - David J. Warne; Ruth E. Baker; Matthew J. Simpson (J. Comput. Graph. Stat., 2022)

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

Explainability of the COVID-19 epidemiological model with nonnegative tensor factorization. - Thirunavukarasu Balasubramaniam; David J. Warne; Richi Nayak; Kerrie L. Mengersen (Int. J. Data Sci. 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)

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)

Efficient multifidelity likelihood-free Bayesian inference with adaptive computational resource allocation. - Thomas P. Prescott; David J. Warne; Ruth E. Baker (J. Comput. Phys., 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)

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)