Publications

Holmes, C. and Walker, S. (2023) “Statistical inference with exchangeability and martingales”, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, 381(2247), p. 20220143.

Robert, C. and Rousseau, J. (2023) “A special issue on Bayesian inference: challenges, perspectives and prospects”, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, 381(2247), p. 20220155.

Dunger‐Baldauf, C. et al. (2023) “Generating the Right Evidence at the Right Time: Principles of a New Class of Flexible Augmented Clinical Trial Designs”, Clinical Pharmacology & Therapeutics, 113(5), pp. 1132–1138.

Donnelly, C. (2023) “Sir David Cox—A Life Well Lived”, Harvard data science review, 5(2).

Lee, J., Miscouridou, X. and Caron, F. (2023) “A unified construction for series representations and finite approximations of completely random measures”, Bernoulli, 29(3), pp. 2142–2166.

Kim, Y., Donnelly, C. and Nouvellet, P. (2023) “Drivers of SARS-CoV-2 testing behaviour: a modelling study using nationwide testing data in England”, Nature Communications, 14.

Elliott, P. et al. (2023) “Design and implementation of a national SARS-CoV-2 monitoring program in England: REACT-1 Study”, American Journal of Public Health, 113(5), pp. 545–554.

Lin, X., Tarp, J. and Evans, R. (2023) “Combining experimental and observational data through a power likelihood.”

De Bortoli, V. et al. (2023) “Riemannian score-based generative modelling”, in Advances in Neural Information Processing Systems 35 (NeurIPS 2022). Curran Associates, pp. 2406–2422.

Naik, C., Rousseau, J. and Campbell, T. (2023) “Fast Bayesian coresets via subsampling and quasi-Newton refinement”, in Advances in Neural Information Processing Systems 35 (NeurIPS 2022). Curran Associates, pp. 70–83.