Publications

Dorigatti, I. et al. (2019) “Risk of yellow fever virus importation into the United States from Brazil, outbreak years 2016–2017 and 2017–2018”, Scientific Reports, 9.

Vaškevičius, T., Kanade, V. and Rebeschini, P. (2019) “Implicit regularization for optimal sparse recovery”, in Advances in Neural Information Processing Systems 32 (NIPS 2019). Neural Information Processing Systems Foundation, pp. 2968–2979.

Teh, Y., Dupont, E. and Doucet, A. (2019) “Augmented neural ODEs”, Proceedings of the 5th Workshop on Energy Efficient Machine Learning and Cognitive Computing - NeurIPS Edition (EMC2-NIPS 2019), 32(2019), pp. 1–11.

Mathieu, E. et al. (2019) “Continuous hierarchical representations with poincaré Variational Auto-Encoder”, in Advances in Neural Information Processing Systems 32: 33rd Conference on Neural Information Processing Systems (NeurIPS 2019). Curran Associates, pp. 12521–12532.

Ge, S. et al. (2019) “Random tessellation forests”, in Advances in Neural Information Processing Systems 32: 33rd Conference on Neural Information Processing Systems (NeurIPS 2019). Curran Associates, pp. 9543–9553.

Foster, A. et al. (2019) “Variational Bayesian optimal experimental design”, in Advances in Neural Information Processing Systems 32 (NIPS 2019). Conference on Neural Information Processing Systems.

Kosiorek, A. et al. (2019) “Stacked capsule autoencoders”, in Advances in Neural Information Processing Systems 32 (NIPS 2019). Nueral Information Processing Systems, p. 15512.

Rao, D. et al. (2019) “Continual unsupervised representation learning”, in Advances in Neural Information Processing Systems 32 (NIPS 2019). Conference on Neural Information Processing Systems.

Foster, A. et al. (2019) “Variational Bayesian Optimal Experimental Design”, in.

Enticott, G. et al. (2019) “An assessment of risk compensation and spillover behavioural adaptions associated with the use of vaccines in animal disease management”, Vaccine, 38(5), pp. 1065–1075.