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Publications

Richards, D. and Rebeschini, P. (2019) “Optimal statistical rates for decentralised non-parametric regression with linear speed-up”, in Advances in Neural Information Processing Systems 32 (NIPS 2019). Neural Information Processing Systems Foundation.
Foster, A. et al. (2019) “A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments.”
Fawsitt, C. et al. (2019) “Cost-effectiveness analysis of baseline testing for resistance-associated polymorphisms to optimize treatment outcome in genotype 1 noncirrhotic treatment-naïve patients with chronic hepatitis C virus”, Value in Health, 23(2), pp. 180–190.
Naik, C., Caron, F. and Rousseau, J. (2019) “Sparse Networks with Core-Periphery Structure”, arXiv.
Naderiparizi, S. et al. (2019) “Amortized Rejection Sampling in Universal Probabilistic Programming”, arXiv.
Downs, S. et al. (2019) “Assessing effects from four years of industry-led badger culling in England on the incidence of bovine tuberculosis in cattle, 2013–2017”, Scientific Reports, 9.
Ham, C. et al. (2019) “Effect of culling on individual badger (Meles meles) behaviour: potential implications for Bovine Tuberculosis transmission”, Journal of Applied Ecology, 56(11), pp. 2390–2399.
Liu, X. et al. (2019) “Reporting guidelines for clinical trials evaluating artificial intelligence interventions are needed”, Nature Medicine, 25(10), pp. 1467–1468.
Eneanya, O. et al. (2019) “Mapping the baseline prevalence of lymphatic filariasis across Nigeria”, Parasites and Vectors, 12, p. Article number: 440.
Vaškevičius, T., Kanade, V. and Rebeschini, P. (2019) “Implicit Regularization for Optimal Sparse Recovery”, arXiv.