Publications

Webb, S. et al. (2019) “A statistical approach to assessing neural network robustness”, in Seventh International Conference on Learning Representations (ICLR 2019). International Conferences on Learning Representations.

Rebeschini, P. and Tatikonda, S. (2019) “A new approach to Laplacian solvers and flow problems”, Journal of Machine Learning Research, 20(36), p. 1−37.

Ayed, F., Lee, J. and Caron, F. (2019) “Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with Double Power-law Behavior”, arXiv.

Nalisnick, E. et al. (2019) “Hybrid models with deep and invertible features”, in 36th International Conference on Machine Learning, ICML 2019, pp. 8295–8304.

Webb, S. et al. (2019) “A statistical approach to assessing neural network robustness”, in 7th International Conference on Learning Representations, ICLR 2019.

Mathieu, E. et al. (2019) “Disentangling disentanglement in variational autoencoders”, in 36th International Conference on Machine Learning, ICML 2019, pp. 7744–7754.

Fong, E., Lyddon, S. and Holmes, C. (2019) “Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap”, in Proceedings of Machine Learning Research, pp. 1952–1962.

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.

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.

Le, T. et al. (2019) “Revisiting reweighted wake-sleep for models with stochastic control flow”, in 35th Conference on Uncertainty in Artificial Intelligence, UAI 2019.