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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.
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.
Rainforth, T. et al. (2019) “On nesting Monte Carlo estimators”, in 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm Sweden, 10th - 15th July 2018. Proceedings of Machine Learning Research, pp. 4267–4276.
Elliott, A. et al. (2019) “Anomaly detection in networks with application to financial transaction networks”, JournalName [Preprint].
Nalisnick, E. et al. (2019) “Do deep generative models know what they don’t know?”, in 7th International Conference on Learning Representations Iclr 2019.
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.
Sodjo, J. et al. (2019) “A Bayesian Nonparametric Model for Unsupervised Joint Segmentation of a Collection of Images”, IEEE Access, 7, pp. 120176–120188.
Ayed, F., Lee, J. and Caron, F. (2019) “Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior”, in 36th International Conference on Machine Learning, ICML 2019, pp. 604–613.