| Bayesopt adversarial attack B Ru, A Cobb, A Blaas, Y Gal International conference on learning representations, 2019 | 93 | 2019 |
| Adversarial attacks on graph classifiers via bayesian optimisation X Wan, H Kenlay, R Ru, A Blaas, MA Osborne, X Dong Advances in Neural Information Processing Systems 34, 6983-6996, 2021 | 29 | 2021 |
| Adversarial robustness guarantees for classification with gaussian processes A Blaas, A Patane, L Laurenti, L Cardelli, M Kwiatkowska, S Roberts International Conference on Artificial Intelligence and Statistics, 3372-3382, 2020 | 19 | 2020 |
| On invariance penalties for risk minimization K Khezeli, A Blaas, F Soboczenski, N Chia, J Kalantari arXiv preprint arXiv:2106.09777, 2021 | 16 | 2021 |
| Prototyping CRISP: a causal relation and inference search platform applied to colorectal cancer data S Budd, A Blaas, A Hoarfrost, K Khezeli, K D'Silva, F Soboczenski, ... 2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech …, 2021 | 15 | 2021 |
| Localised kinky inference A Blaas, JM Manzano, D Limon, J Calliess 2019 18th European Control Conference (ECC), 985-992, 2019 | 15 | 2019 |
| The role of entropy and reconstruction in multi-view self-supervised learning BR Gálvez, A Blaas, P Rodríguez, A Golinski, X Suau, J Ramapuram, ... International Conference on Machine Learning, 29143-29160, 2023 | 12 | 2023 |
| Robustness quantification for classification with gaussian processes A Blaas, L Laurenti, A Patane, L Cardelli, M Kwiatkowska, S Roberts arXiv preprint arXiv:1905.11876, 2019 | 10 | 2019 |
| Adversarial robustness guarantees for gaussian processes A Patane, A Blaas, L Laurenti, L Cardelli, S Roberts, M Kwiatkowska Journal of Machine Learning Research 23 (146), 1-55, 2022 | 8 | 2022 |
| Duet: 2d structured and approximately equivariant representations X Suau, F Danieli, TA Keller, A Blaas, C Huang, J Ramapuram, ... arXiv preprint arXiv:2306.16058, 2023 | 5 | 2023 |
| Considerations for distribution shift robustness in health A Blaas, A Miller, L Zappella, JH Jacobsen, C Heinze-Deml ICLR 2023 Workshop on Trustworthy Machine Learning for Healthcare, 2023 | 3 | 2023 |
| Challenges of adversarial image augmentations A Blaas, X Suau, J Ramapuram, N Apostoloff, L Zappella I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, 9-14, 2022 | 3 | 2022 |
| Scalable bounding of predictive uncertainty in regression problems with SLAC A Blaas, AD Cobb, JP Calliess, SJ Roberts Scalable Uncertainty Management: 12th International Conference, SUM 2018 …, 2018 | 3 | 2018 |
| The Effect of Prior Lipschitz Continuity on the Adversarial Robustness of Bayesian Neural Networks A Blaas, SJ Roberts arXiv preprint arXiv:2101.02689, 2021 | 1 | 2021 |
| On the adversarial robustness of Bayesian machine learning models AC Blaas University of Oxford, 2021 | 1 | 2021 |
| Controlling Language and Diffusion Models by Transporting Activations P Rodriguez, A Blaas, M Klein, L Zappella, N Apostoloff, M Cuturi, X Suau arXiv preprint arXiv:2410.23054, 2024 | | 2024 |
| Considerations for Distribution Shift Robustness of Diagnostic Models in Healthcare A Blaas, A Goliński, A Miller, L Zappella, JH Jacobsen, C Heinze-Deml arXiv preprint arXiv:2410.19575, 2024 | | 2024 |
| Robust multimodal models have outlier features and encode more concepts J Crabbé, P Rodríguez, V Shankar, L Zappella, A Blaas arXiv preprint arXiv:2310.13040, 2023 | | 2023 |
| Interpreting CLIP: Insights on the Robustness to ImageNet Distribution Shifts J Crabbé, P Rodriguez, V Shankar, L Zappella, A Blaas Transactions on Machine Learning Research, 0 | | |
| On Information Maximisation in Multi-View Self-Supervised Learning BR Gálvez, A Blaas, X Suau, J Ramapuram, D Busbridge, L Zappella | | |