Publications

Kendall, M. et al. (2020) “Epidemiological changes on the Isle of Wight after the launch of the NHS Test and Trace programme: a preliminary analysis”, The Lancet Digital Health, 2(12), pp. e658 - e666.

Richards, D., Rebeschini, P. and Rosasco, L. (2020) “Decentralised learning with distributed gradient descent and random features”, in Proceedings of the 37th International Conference on Machine Learning. Proceedings of Machine Learning Research, pp. 8105–8115.

Klimm, F. et al. (2020) “Functional module detection through integration of single-cell RNA sequencing data with protein–protein interaction networks”, BMC Genomics, 21(1).

Wu, F. and Rebeschini, P. (2020) “A Continuous-Time Mirror Descent Approach to Sparse Phase Retrieval”, arXiv.

Schwessinger, R. et al. (2020) “DeepC: Predicting 3D genome folding using megabase-scale transfer learning”, Nature Methods, 17(11), pp. 1118–1124.

Watson, J. et al. (2020) “A cautionary note on the use of unsupervised machine learning algorithms to characterise malaria parasite population structure from genetic distance matrices”, PLoS Genetics, 16(10).

Wang, Q., Rao, V. and Teh, Y. (2020) “An exact auxiliary variable Gibbs sampler for a class of diffusions”, Journal of Computational and Graphical Statistics, 30(2), pp. 297–311.

O’Cathail, S. et al. (2020) “NRF2 metagene signature is a novel prognostic biomarker in colorectal cancer”, Cancer Genetics, 248, pp. 1–10.

Pompe, E., Holmes, C. and Łatuszyński, K. (2020) “A framework for adaptive MCMC targeting multimodal distributions”, The Annals of Statistics, 48(5), pp. 2930–2952.

Mateen, B. et al. (2020) “Improving the quality of machine learning in health applications and clinical research”, Nature Machine Intelligence, 2(10), pp. 554–556.