Publications
Hutchinson, M. et al. (2021) “LieTransformer: Equivariant Self-Attention for Lie Groups”, in Proceedings of Machine Learning Research, pp. 4533–4543.
Rudner, T. et al. (2021) “On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations”, in Advances in Neural Information Processing Systems, pp. 28376–28389.
Holderrieth, P., Hutchinson, M. and Teh, Y. (2021) “Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes”, in Proceedings of Machine Learning Research, pp. 4297–4307.
Mathieu, E., Foster, A. and Teh, Y. (2021) “On Contrastive Representations of Stochastic Processes”, in Advances in Neural Information Processing Systems, pp. 28823–28835.
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.
Fong, E. and Holmes, C. (2021) “Conformal Bayesian Computation”, in Advances in Neural Information Processing Systems, pp. 18268–18279.