Publications

Behr, M., Holmes, C. and Munk, A. (2018) “Multiscale blind source separation”, The Annals of Statistics, 46(2), pp. 711–744.

Kafkafi, N. et al. (2018) “Reproducibility and replicability of rodent phenotyping in preclinical studies”, Neuroscience and biobehavioral reviews, 87, pp. 218–232.

Rowland, M. et al. (2018) “An analysis of categorical distributional reinforcement learning”, in International Conference on Artificial Intelligence and Statistics, AISTATS 2018, pp. 29–37.

Abdalla, M. et al. (2018) “A general framework for predicting the transcriptomic consequences of non-coding variation.”

Geladaki, A. et al. (2018) “LOPIT-DC: A simpler approach to high-resolution spatial proteomics”, bioRxiv.

Crook, O. et al. (2018) “A Bayesian Mixture Modelling Approach For Spatial Proteomics”, bioRxiv.

Kim, H. and Teh, Y. (2018) “Scaling up the automatic statistician: Scalable structure discovery using gaussian processes”, in International Conference on Artificial Intelligence and Statistics, AISTATS 2018, pp. 575–584.

Rainforth, T. et al. (2018) “Tighter variational bounds are not necessarily better”, in 35th International Conference on Machine Learning, ICML 2018.

Webb, S. et al. (2018) “Faithful inversion of generative models for effective amortized inference”, in Advances in Neural Information Processing Systems.

Gamelo, M. et al. (2018) “Conditional neural processes”, in 35th International Conference on Machine Learning, ICML 2018, pp. 2738–2747.