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Publications

Eric, N. et al. (2019) “Hybrid models with deep and invertible features”, in Proceedings of Machine Learning Research. Proceedings of Machine Learning Research, pp. 4723–4732.
Lee, J. et al. (2019) “Set transformer: A framework for attention-based permutation-invariant neural networks”, in Proceedings of Machine Learning Research. PMLR, pp. 3744–3753.
Lyddon, S., Holmes, C. and Walker, S. (2019) “General Bayesian updating and the loss-likelihood bootstrap”, Biometrika, 106(2), pp. 465–478.
Gram-Hansen, B. et al. (2019) “Hijacking Malaria Simulators with Probabilistic Programming”, arXiv.
Lee, J., Miscouridou, X. and Caron, F. (2019) “A unified construction for series representations and finite approximations of completely random measures”, arXiv.
Lee, J. et al. (2019) “Set transformer: A framework for attention-based permutation-invariant neural networks”, in. Proceedings of Machine Learning Research, pp. 3744–3753.
Richards, D. and Rebeschini, P. (2019) “Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up”, arXiv.
Merel, J. et al. (2019) “Neural probabilistic motor primitives for humanoid control”, in International Conference on Learning Representations.
Nalisnick, E. et al. (2019) “Do deep generative models know what they don’t know?”, in International Conference on Learning Representations.
Eneanya, O., Garske, T. and Donnelly, C. (2019) “The social, physical and economic impact of lymphedema and hydrocele: A matched cross-sectional study in rural Nigeria”, BMC Infectious Diseases, 19.