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Publications

Nalisnick, E. et al. (2019) “Hybrid models with deep and invertible features”, in 36th International Conference on Machine Learning Icml 2019, pp. 8295–8304.
Fong, E., Lyddon, S. and Holmes, C. (2019) “Scalable nonparametric sampling from multimodal posteriors with the posterior bootstrap”, in 36th International Conference on Machine Learning, ICML 2019, pp. 3443–3464.
Sodjo, J. et al. (2019) “A Bayesian Nonparametric Model for Unsupervised Joint Segmentation of a Collection of Images”, IEEE Access, 7, pp. 120176–120188.
Mitrovic, J., Sejdinovic, D. and Teh, Y. (2019) “Deep kernel machines via the kernel reparametrization trick”, in 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings.
Kim, H. et al. (2019) “Attentive neural processes”, in 7th International Conference on Learning Representations, ICLR 2019.
Maddison, C. et al. (2019) “Particle value functions”, in 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings.
Collaborative, S. et al. (2019) “Critical care usage after major gastrointestinal and liver surgery: a prospective, multicentre observational study”, British Journal of Anaesthesia, 122(1), pp. 42–50.
Ayed, F., Lee, J. and Caron, F. (2019) “Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior”, in Proceedings of Machine Learning Research, pp. 395–404.
Lee, J. et al. (2019) “A Bayesian model for sparse graphs with flexible degree distribution and overlapping community structure”, in Proceedings of Machine Learning Research, pp. 758–767.
Zhou, Y. et al. (2019) “LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models”, in Proceedings of Machine Learning Research, pp. 148–157.