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Publications

Wilde, H. et al. (2021) “Foundations of Bayesian Learning from Synthetic Data”, in Proceedings of Machine Learning Research, pp. 541–549.
Naik, C., Caron, F. and Rousseau, J. (2021) “Sparse networks with core-periphery structure”, Electronic Journal of Statistics, 15(1), pp. 1814–1868.
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.
Thompson, H. et al. (2020) “SARS-CoV-2 infection prevalence on repatriation flights from Wuhan City, China”, Journal of Travel Medicine, 27(8), p. 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”, p. 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.
Vaškevičius, T., Kanade, V. and Rebeschini, P. (2020) “The statistical complexity of early-stopped mirror descent”, in. Neural Information Processing Systems Foundation, Inc., pp. 1–12.