Publications (Statistical Theory and Methodology) | Department of Statistics - University of Oxford

Publications

Martin, N. et al. (2022) “A graph based neural network approach to immune profiling of multiplexed tissue samples”, pp. 3063–3067.

Mullins, E. et al. (2022) “Tracking the incidence and risk factors for SARS-CoV-2 infection using historical maternal booking serum samples”, PLoS ONE, 17(9).

Ezanno, P. et al. (2022) “The African swine fever modelling challenge: Model comparison and lessons learnt”, Epidemics, 40, p. 100615.

Eales, O. et al. (2022) “Appropriately smoothing prevalence data to inform estimates of growth rate and reproduction number”, Epidemics, 40, p. 100604.

Parag, K., Donnelly, C. and Zarebski, A. (2022) “Quantifying the information in noisy epidemic curves”, Nature Computational Science, 2(9), pp. 584–594.

Tirumala, D. et al. (2022) “Behavior Priors for Efficient Reinforcement Learning”, Journal of Machine Learning Research, 23.

Dankwa, E. et al. (2022) “Stochastic modelling of African swine fever in wild boar and domestic pigs: epidemic forecasting and comparison of disease management strategies”, Epidemics, 40.

Nicholson, G. et al. (2022) “Multivariate phenotype analysis enables genome-wide inference of mammalian gene function”, PLOS Biology, 20(8), p. e3001723.

Elliott, P. et al. (2022) “Dynamics of a national Omicron SARS-CoV-2 epidemic during January 2022 in England”, Nature Communications, 13(1), pp. 4500–4500.

Atchison, C. et al. (2022) “Validity of self-testing at home with rapid severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody detection by lateral flow immunoassay”, Clinical Infectious Diseases, 76(4).