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.
Xu, W. and Reinert, G. (2021) “A Stein Goodness-of-fit Test for Exponential Random Graph Models”, in Proceedings of Machine Learning Research, pp. 415–423.
Camuto, A. et al. (2021) “Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections”, in Proceedings of Machine Learning Research, pp. 1249–1260.
Ghalebikesabi, S. et al. (2021) “On Locality of Local Explanation Models”, in Advances in Neural Information Processing Systems, pp. 18395–18407.
Fong, E. and Holmes, C. (2021) “Conformal Bayesian Computation”, in Advances in Neural Information Processing Systems, pp. 18268–18279.
Chau, S. et al. (2021) “BAYESIMP: Uncertainty Quantification for Causal Data Fusion”, in Advances in Neural Information Processing Systems, pp. 3466–3477.
Zaidi, S. et al. (2021) “Neural Ensemble Search for Uncertainty Estimation and Dataset Shift”, in Advances in Neural Information Processing Systems, pp. 7898–7911.