Publications
Willetts, M. et al. (2021) “IMPROVING VAES’ ROBUSTNESS TO ADVERSARIAL ATTACK”, in ICLR 2021 - 9th International Conference on Learning Representations.
Ghalebikesabi, S. et al. (2021) “On Locality of Local Explanation Models”, in Advances in Neural Information Processing Systems, pp. 18395–18407.
Hayou, S. et al. (2021) “ROBUST PRUNING AT INITIALIZATION”, in Iclr 2021 9th International Conference on Learning Representations.
Foster, A. et al. (2021) “Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design”, in Proceedings of Machine Learning Research, pp. 3384–3395.
Rudner, T. et al. (2021) “On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes”, in Proceedings of Machine Learning Research, pp. 9148–9156.
Kossen, J. et al. (2021) “Active Testing: Sample-Efficient Model Evaluation”, in Proceedings of Machine Learning Research, pp. 5753–5763.
Wang, B., Webb, S. and Rainforth, T. (2021) “Statistically Robust Neural Network Classification”, in Proceedings of Machine Learning Research, pp. 1735–1745.
Xu, J. et al. (2021) “Group Equivariant Subsampling”, in Advances in Neural Information Processing Systems, pp. 5934–5946.
Xu, J. et al. (2021) “Group Equivariant Subsampling”, in Advances in Neural Information Processing Systems, pp. 5934–5946.
Tolpin, D. et al. (2021) “Probabilistic Programs with Stochastic Conditioning”, in Proceedings of Machine Learning Research, pp. 10312–10323.