Publications
Foster, A., Pukdee, R. and Rainforth, T. (2021) “IMPROVING TRANSFORMATION INVARIANCE IN CONTRASTIVE REPRESENTATION LEARNING”, in ICLR 2021 - 9th International Conference on Learning Representations.
Willetts, M. et al. (2021) “IMPROVING VAES’ ROBUSTNESS TO ADVERSARIAL ATTACK”, in ICLR 2021 - 9th International Conference on Learning Representations.
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 37th Conference on Uncertainty in Artificial Intelligence, UAI 2021, pp. 1735–1745.
Kossen, J. et al. (2021) “Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning”, in Advances in Neural Information Processing Systems, pp. 28742–28756.
Xu, J. et al. (2021) “Group Equivariant Subsampling”, in Advances in Neural Information Processing Systems, pp. 5934–5946.
Willetts, M. et al. (2021) “IMPROVING VAES’ ROBUSTNESS TO ADVERSARIAL ATTACK”, in ICLR 2021 - 9th International Conference on Learning Representations.
Farquhar, S., Gal, Y. and Rainforth, T. (2021) “ON STATISTICAL BIAS IN ACTIVE LEARNING: HOW AND WHEN TO FIX IT”, in ICLR 2021 - 9th International Conference on Learning Representations.
Tolpin, D. et al. (2021) “Probabilistic Programs with Stochastic Conditioning”, in Proceedings of Machine Learning Research, pp. 10312–10323.
Fong, E. and Holmes, C. (2021) “Conformal Bayesian Computation”, in Advances in Neural Information Processing Systems, pp. 18268–18279.