Publications
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.
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.
Ivanova, D. et al. (2021) “Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods”, in Advances in Neural Information Processing Systems, pp. 25785–25798.
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.
Willetts, M. et al. (2021) “IMPROVING VAES’ ROBUSTNESS TO ADVERSARIAL ATTACK”, 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.
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.
Klimm, F., Deane, C. and Reinert, G. (2021) “Hypergraphs for predicting essential genes using multiprotein complex data”, J. Complex Networks, 9.
Ton, J. et al. (2021) “Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings”, in Proceedings of Machine Learning Research, pp. 1099–1107.