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University of Oxford, Department of Statistics logo
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Publications

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. PMLR, pp. 758–767.
Hejblum, B. et al. (2019) “Sequential Dirichlet process mixtures of multivariate skew t-distributions for model-based clustering of flow cytometry data”, Annals of Applied Statistics, 13(1), pp. 638–660.
Galashov, A. et al. (2019) “Meta-Learning surrogate models for sequential decision making.”
Zecchin, B. et al. (2019) “Genetic and spatial characterization of the red fox (Vulpes vulpes) population in the area stretching between the Eastern and Dinaric Alps and its relationship with rabies and canine distemper dynamics”, PloS One, 14(3).
Ayed, F. and Caron, F. (2019) “Nonnegative Bayesian nonparametric factor models with completely random measures for community detection”, arXiv.
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.
Suwannahitatorn, P. et al. (2019) “Uncooked fish consumption among those at risk of Opisthorchis viverrini infection in central Thailand”, PloS ONE, 14(1).
Nalisnick, E. et al. (2019) “Do deep generative models know what they don’t know?”, in 7th International Conference on Learning Representations Iclr 2019.