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University of Oxford, Department of Statistics logo
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Publications

Fu, H. et al. (2021) “Database of epidemic trends and control measures during the first wave of COVID-19 in mainland China”, International Journal of Infectious Diseases, 102, pp. 463–471.
Hillis, S. et al. (2021) “Under the Radar: Global Minimum Estimates for COVID-19-Associated Orphanhood and Deaths Among Caregivers During 2020”, SSRN Electronic Journal.
Unwin, H. et al. (2021) “More than 5.2 Million Children Affected by Global Surges in COVID-Associated Orphanhood and Caregiver Death: New Evidence for National Responses”, SSRN Electronic Journal.
Mullins, E. et al. (2021) “Tracking the Incidence and Risk Factors for Sars-Cov-2 Infection in North West London by Detection of Antibody in Historical Maternal Booking Serum Samples”, SSRN Electronic Journal.
Thompson, H. et al. (2020) “SARS-CoV-2 infection prevalence on repatriation flights from Wuhan City, China”, Journal of Travel Medicine, 27(8), pp. taaa135 - taaa135-.
Di Benedetto, G., Caron, F. and Teh, Y. (2020) “Non-exchangeable random partition models for microclustering”. University of Oxford.
Di Benedetto, G., Caron, F. and Teh, Y. (2020) “Non-exchangeable random partition models for microclustering”. University of Oxford.
Riley, S. et al. (2020) “REACT-1 round 7 updated report: regional heterogeneity in changes in prevalence of SARS-CoV-2 infection during the second national COVID-19 lockdown in England”, pp. 2020.12.15.20248244 – 2020.12.15.20248244.
Willetts, M., Roberts, S. and Holmes, C. (2020) “Semi-Unsupervised Learning: Clustering and Classifying using Ultra-Sparse Labels”, in. Institute of Electrical and Electronics Engineers (IEEE), pp. 5286–5295.
Wu, F. and Rebeschini, P. (2020) “A continuous-time mirror descent approach to sparse phase retrieval”, in Advances in Neural Information Processing Systems 33 (NeurIPS 2020). Neural Information Processing Systems Foundation, Inc., pp. 1–12.