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Publications

Schwarz, J. et al. (2021) “Powerpropagation: A sparsity inducing weight reparameterisation”, in Advances in Neural Information Processing Systems, pp. 28889–28903.
Hutchinson, M. et al. (2021) “Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independant Projected Kernels”, in Advances in Neural Information Processing Systems, pp. 17160–17169.
Ghalebikesabi, S. et al. (2021) “Deep Generative Missingness Pattern-Set Mixture Models”, in Proceedings of Machine Learning Research, pp. 3727–3735.
Wilde, H. et al. (2021) “Foundations of Bayesian Learning from Synthetic Data”, in Proceedings of Machine Learning Research, pp. 541–549.
Camuto, A. et al. (2021) “Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections”, in Proceedings of Machine Learning Research, pp. 1249–1260.
Fu, H. et al. (2021) “Database of epidemic trends and control measures during the first wave of COVID-19 in mainland China”, International Journal of Infectious Diseases, 102, pp. 463–471.
Fong, E. and Holmes, C. (2021) “Conformal Bayesian Computation”, in Advances in Neural Information Processing Systems, pp. 18268–18279.
Ghalebikesabi, S. et al. (2021) “On Locality of Local Explanation Models”, in Advances in Neural Information Processing Systems, pp. 18395–18407.
Verity, R. et al. (2021) “COVID-19 and the difficulty of inferring epidemiological parameters from clinical data – Authors’ reply”, The Lancet Infectious Diseases, 21(1), pp. 28 – 28.
Chau, S. et al. (2021) “BAYESIMP: Uncertainty Quantification for Causal Data Fusion”, in Advances in Neural Information Processing Systems, pp. 3466–3477.