Arno Blaas

According to our database, Arno Blaas authored at least 17 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Controlling Language and Diffusion Models by Transporting Activations.

Pau Rodríguez López, Arno Blaas, Michal Klein, Luca Zappella, Nicholas Apostoloff, Marco Cuturi, Xavier Suau

CoRR, 2024

Considerations for Distribution Shift Robustness of Diagnostic Models in Healthcare.

Arno Blaas, Adam Golinski, Andrew C. Miller, Luca Zappella, Jörn-Henrik Jacobsen, Christina Heinze-Deml

CoRR, 2024

2023

Robust multimodal models have outlier features and encode more concepts.

Jonathan Crabbé, Pau Rodríguez, Vaishaal Shankar, Luca Zappella, Arno Blaas

CoRR, 2023

DUET: 2D Structured and Approximately Equivariant Representations.

Xavier Suau, Federico Danieli, T. Anderson Keller, Arno Blaas, Chen Huang, Jason Ramapuram, Dan Busbridge, Luca Zappella

Proceedings of the International Conference on Machine Learning, 2023

The Role of Entropy and Reconstruction in Multi-View Self-Supervised Learning.

Borja Rodríguez Gálvez, Arno Blaas, Pau Rodríguez, Adam Golinski, Xavier Suau, Jason Ramapuram, Dan Busbridge, Luca Zappella

Proceedings of the International Conference on Machine Learning, 2023

2022

Adversarial Robustness Guarantees for Gaussian Processes.

Andrea Patane, Arno Blaas, Luca Laurenti, Luca Cardelli, Stephen Roberts, Marta Kwiatkowska

J. Mach. Learn. Res., 2022

2021

Adversarial Attacks on Graph Classification via Bayesian Optimisation.

Xingchen Wan, Henry Kenlay, Binxin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong

CoRR, 2021

On Invariance Penalties for Risk Minimization.

Kia Khezeli, Arno Blaas, Frank Soboczenski, Nicholas Chia, John Kalantari

CoRR, 2021

The Effect of Prior Lipschitz Continuity on the Adversarial Robustness of Bayesian Neural Networks.

Arno Blaas, Stephen J. Roberts

CoRR, 2021

Adversarial Attacks on Graph Classifiers via Bayesian Optimisation.

Xingchen Wan, Henry Kenlay, Robin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Prototyping CRISP: A Causal Relation and Inference Search Platform applied to Colorectal Cancer Data.

Samuel Budd, Arno Blaas, Adrienne Hoarfrost, Kia Khezeli, Krittika D'Silva, Frank Soboczenski, Graham Mackintosh, Nicholas Chia, John Kalantari

Proceedings of the 3rd IEEE Global Conference on Life Sciences and Technologies, 2021

Challenges of Adversarial Image Augmentations.

Arno Blaas, Xavier Suau, Jason Ramapuram, Nicholas Apostoloff, Luca Zappella

Proceedings of the I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, 2021

2020

BayesOpt Adversarial Attack.

Binxin Ru, Adam D. Cobb, Arno Blaas, Yarin Gal

Proceedings of the 8th International Conference on Learning Representations, 2020

Adversarial Robustness Guarantees for Classification with Gaussian Processes.

Arno Blaas, Andrea Patane, Luca Laurenti, Luca Cardelli, Marta Kwiatkowska, Stephen J. Roberts

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Robustness Quantification for Classification with Gaussian Processes.

Arno Blaas, Luca Laurenti, Andrea Patane, Luca Cardelli, Marta Kwiatkowska, Stephen J. Roberts

CoRR, 2019

Localised Kinky Inference.

Arno Blaas, José María Manzano, Daniel Limón, Jan Calliess

Proceedings of the 17th European Control Conference, 2019

2018

Scalable Bounding of Predictive Uncertainty in Regression Problems with SLAC.

Arno Blaas, Adam D. Cobb, Jan-Peter Calliess, Stephen J. Roberts

Proceedings of the Scalable Uncertainty Management - 12th International Conference, 2018