Arno Blaas
Arno Blaas
Apple MLR
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Cited by
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Bayesopt adversarial attack
B Ru, A Cobb, A Blaas, Y Gal
International conference on learning representations, 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
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
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
On invariance penalties for risk minimization
K Khezeli, A Blaas, F Soboczenski, N Chia, J Kalantari
arXiv preprint arXiv:2106.09777, 2021
Localised kinky inference
A Blaas, JM Manzano, D Limon, J Calliess
2019 18th European Control Conference (ECC), 985-992, 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
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
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
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
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
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
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
The Effect of Prior Lipschitz Continuity on the Adversarial Robustness of Bayesian Neural Networks
A Blaas, SJ Roberts
arXiv preprint arXiv:2101.02689, 2021
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
On the adversarial robustness of Bayesian machine learning models
AC Blaas
University of Oxford, 2021
On Information Maximisation in Multi-View Self-Supervised Learning
BR Gálvez, A Blaas, X Suau, J Ramapuram, D Busbridge, L Zappella
Attacking Graph Classification via Bayesian Optimisation
X Wan, H Kenlay, B Ru, A Blaas, M Osborne, X Dong
ICML 2021 Workshop on Adversarial Machine Learning, 0
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