Publications

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.

Watson, J. and Holmes, C. (2020) “Machine learning analysis plans for randomised controlled trials: detecting treatment effect heterogeneity with strict control of type I error”, Trials, 21(1), p. 156.

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.

Watson, J. and Holmes, C. (2020) “Correction to: Graphing and reporting heterogeneous treatment effects through reference classes”, Trials, 21(1), p. 865.

Watson, J. and Holmes, C. (2020) “Graphing and reporting heterogeneous treatment effects through reference classes”, Trials, 21(1), p. 386.

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).