Publications

Rao, D. et al. (2019) “Continual unsupervised representation learning”, in Advances in Neural Information Processing Systems 32 (NIPS 2019). Conference on Neural Information Processing Systems.

Locatello, F. et al. (2019) “On the fairness of disentangled representations”, in Advances in Neural Information Processing Systems. NeurIPS.

Foster, A. et al. (2019) “Variational Bayesian Optimal Experimental Design”, in.

Richards, D. and Rebeschini, P. (2019) “Optimal statistical rates for decentralised non-parametric regression with linear speed-up”, in Advances in Neural Information Processing Systems 32 (NIPS 2019). Neural Information Processing Systems Foundation.

Martínez-Rubio, D., Kanade, V. and Rebeschini, P. (2019) “Decentralized cooperative stochastic bandits”, in Advances in Neural Information Processing Systems 32. Neural Information Processing Systems Foundation.

Foster, A. et al. (2019) “A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments.”

Fawsitt, C. et al. (2019) “Cost-effectiveness analysis of baseline testing for resistance-associated polymorphisms to optimize treatment outcome in genotype 1 noncirrhotic treatment-naïve patients with chronic hepatitis C virus”, Value in Health, 23(2), pp. 180–190.

Naik, C., Caron, F. and Rousseau, J. (2019) “Sparse Networks with Core-Periphery Structure”, arXiv.

Naderiparizi, S. et al. (2019) “Amortized Rejection Sampling in Universal Probabilistic Programming”, arXiv.