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Publications

Jeffrey, B. et al. (2020) “Anonymised and aggregated crowd level mobility data from mobile phones suggests that initial compliance with COVID-19 social distancing interventions was high and geographically consistent across the UK”, Wellcome Open Research, 5, pp. 170 – 170.
Jeffrey, B. et al. (2020) “Anonymised and aggregated crowd level mobility data from mobile phones suggests that initial compliance with COVID-19 social distancing interventions was high and geographically consistent across the UK”, Wellcome Open Research, 5, p. 170.
Hawryluk, I. et al. (2020) “Inference of COVID-19 epidemiological distributions from Brazilian hospital data”, pp. 2020.07.15.20154617 – 2020.07.15.20154617.
Parag, K. et al. (2020) “An exact method for quantifying the reliability of end-of-epidemic declarations in real time”, pp. 2020.07.13.20152082 – 2020.07.13.20152082.
Zhou, Y. et al. (2020) “Divide, conquer, and combine: a new inference strategy for probabilistic programs with stochastic support”, in ICML 2020. ICML Proceedings.
Investigators, R. et al. (2020) “Community prevalence of SARS-CoV-2 virus in England during May 2020: REACT study”, pp. 2020.07.10.20150524 – 2020.07.10.20150524.
Miguel, E. et al. (2020) “A systemic approach to assess the potential and risks of wildlife culling for infectious disease control”, Communications Biology, 3.
Richards, D., Rebeschini, P. and Rosasco, L. (2020) “Decentralised Learning with Random Features and Distributed Gradient Descent”, arXiv.
Parag, K. and Donnelly, C. (2020) “Using information theory to optimise epidemic models for real-time prediction and estimation”, PLOS Computational Biology, 16(7), pp. e1007990 - e1007990-.
Thompson, R. et al. (2020) “Key Questions for Modelling COVID-19 Exit Strategies”, arXiv.