Publications

Bickford Smith, F., Foster, A. and Rainforth, T. (2024) “Making better use of unlabelled data in Bayesian Active learning”, in Proceedings of The 27th International Conference on Artificial Intelligence and Statistics. Journal of Machine Learning Research, pp. 847–855.

Falck, F. et al. (2024) “A framework for longitudinal latent factor modelling of treatment response in clinical trials with applications to Psoriatic Arthritis and Rheumatoid Arthritis”, Journal of Biomedical Informatics, 154.

Benton, J. et al. (2024) “Authors’ reply to the Discussion of ‘From denoising diffusions to denoising Markov models’ at the Discussion Meeting on ‘Probabilistic and statistical aspects of machine learning’”, Journal of the Royal Statistical Society Series B (Statistical Methodology), 86(2), pp. 335–339.

Benton, J. et al. (2024) “From denoising diffusions to denoising Markov models”, Journal of the Royal Statistical Society Series B (Statistical Methodology), 86(2), pp. 286–301.

Reinert, G. and Xu, W. (2024) “SteinGen: Generating Fidelitous and Diverse Graph Samples.”

Goldberg, C. et al. (2024) “To do no harm — and the most good — with AI in health care”, Nature Medicine, 30(3), pp. 623–627.

Rainforth, T. et al. (2024) “Modern Bayesian experimental design”, Statistical Science, 39(1), pp. 100–114.

Benton, J., Deligiannidis, G. and Doucet, A. (2024) “Error bounds for flow matching methods”, Transactions on Machine Learning Research [Preprint].

Liu, X. et al. (2024) “Directrices para presentación de informes de ensayos clínicos sobre intervenciones con inteligencia artificial: extensión CONSORT-AI”, BULL PAN AM HEALTH ORGAN, 48, p. e13.

Phillips, A. et al. (2024) “Particle Denoising Diffusion Sampler”, arXiv.