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Publications

Dupont, E. et al. (2022) “COIN++: neural compression across modalities”, Transactions on Machine Learning Research, 2022(11).
Eales, O. et al. (2022) “SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2”, BMC Infectious Diseases, 22(1), pp. 647 – 647.
Charniga, K. et al. (2022) “Estimating Zika virus attack rates and risk of Zika virus-associated neurological complications in Colombian capital cities with a Bayesian model”, Royal Society Open Science, 9(11).
Eales, O. et al. (2022) “Trends in SARS-CoV-2 infection prevalence during England’s roadmap out of lockdown, January to July 2021”, PLoS Computational Biology, 18(11).
Parag, K., Thompson, R. and Donnelly, C. (2022) “Authors’ reply to the discussion of ‘Are epidemic growth rates more informative than reproduction numbers?’ by Parag et al. in Session 1 of the Royal Statistical Society’s Special Topic Meeting on COVID-19 Transmission: 9 June 2021”, Journal of the Royal Statistical Society: Statistics in Society Series A, 185(S1), pp. S55 - S60.
Wu, F. and Rebeschini, P. (2022) “Nearly minimax-optimal rates for noisy sparse phase retrieval via early-stopped mirror descent”, Information and Inference: a Journal of the IMA, 12(2), pp. 633–713.
Whitaker, M. et al. (2022) “Variant-specific symptoms of COVID-19 in a study of 1,542,510 adults in England”, Nature Communications, 13.
Teh, Y. et al. (2022) “Authors’ Reply to the Discussion of ‘Efficient Bayesian Inference of Instantaneous Reproduction Numbers at Fine Spatial Scales, with an Application to Mapping and Nowcasting the Covid-19 Epidemic in British Local Authorities’ by Teh et al. in Session 2 of the Royal Statistical Society’s Special Topic Meeting on COVID-19 Transmission: 11 June 2021”, Journal of the Royal Statistical Society Series A (Statistics in Society), 185(Supplement_1), pp. s107 - s109.
Dankwa, E., Brouwer, A. and Donnelly, C. (2022) “Structural identifiability of compartmental models for infectious disease transmission is influenced by data type”, Epidemics, 41.
Unwin, H. et al. (2022) “Using next generation matrices to estimate the proportion of infections that are not detected in an outbreak”, Epidemics, 41.