Publications

Rainforth, T. (2018) “Nesting probabilistic programs”, in Uncertainty in Artificial Intelligence (UAI). Association for Uncertainty in Artificial Intelligence.

Bloem-Reddy, B. et al. (2018) “Sampling and inference for beta neutral-to-the-left models of sparse networks”, in Uncertainty in Artificial Intelligence: Proceedings of the Thirty-Fourth Conference (2018). AUAI Press, pp. 477–486.

Xu, J. and Teh, Y. (2018) “Controllable Semantic Image Inpainting.”

Jewson, J., Smith, J. and Holmes, C. (2018) “Principles of Bayesian inference using general divergence criteria”, Entropy, 20(6), p. 442.

Czarnecki, W. et al. (2018) “Mix&Match - Agent Curricula for Reinforcement Learning.”

Holmes, C. and Watson, J. (2018) “Machine learning for randomised controlled trials: identifying treatment effectheterogeneity with strict control of type I error”, p. 330795.

Rebeschini, P. and Tatikonda, S. (2018) “Locality in network optimization”, IEEE Transactions on Control of Network Systems, 6(2), pp. 487–500.

Battiston, M. et al. (2018) “A characterization of product-form exchangeable feature probability functions”, Annals of Applied Probability, 28(3), pp. 1423–1448.

Tatikonda, S. and Rebeschini, P. (2018) “Accelerated consensus via Min-Sum Splitting”, in Advances in Neural Information Processing Systems 30: 31st Annual Conference on Neural Information Processing Systems (NIPS 2017). Curran Associates, pp. 1375–1385.

Brown, S. et al. (2018) “High-throughput mouse phenomics for characterizing mammalian gene function”, Nature Reviews Genetics, 19(6), pp. 357–370.