Publications

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

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.

Le, T. et al. (2019) “Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow”, in Proceedings of Machine Learning Research, pp. 1039–1049.

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.

Mathieu, E. et al. (2019) “Disentangling Disentanglement in Variational Autoencoders”, in Proceedings of Machine Learning Research, pp. 4402–4412.