Project Publications
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18 publications:
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[PBL+22]
Andrea Patane, Arno Blaas, Luca Laurenti, Luca Cardelli, Stephen Roberts and Marta Kwiatkowska.
Adversarial Robustness Guarantees for Gaussian Processes.
Journal of Machine Learning Research, 23, pages 1-55.
2022.
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[GPL+22]
Shadi Ghiasi, Andrea Patane, Luca Laurenti, Claudio Gentili, Enzo Pasquale Scilingo, Alberto Greco and Marta Kwiatkowska.
Physiologically-Informed Gaussian Processes for Interpretable Modelling of Psycho-Physiological States.
EEE Journal of Biomedical and Health Informatics (J-BHI).
2022.
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[PPK18]
N. Paoletti, A. Patane and M. Kwiatkowska.
Closed-loop quantitative verification of rate-adaptive pacemakers.
ACM Transactions on Cyber-Physical Systems.
2018.
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[RPL+18b]
S. Rosa, A. Patane, X. Lu, and N. Trigoni.
Semantic Place Understanding for Human--Robot Coexistence—Toward Intelligent Workplaces.
IEEE Transactions on Human-Machine Systems.
2018.
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[DPA+18]
Colombo Desiree and Azucena Garcia Palacios and Javier Fernandez Alvarez and Andrea Patane and Michelle Semonella and Pietro Cipresso and Marta Kwiatkowska and Giuseppe Riva and Cristina Botella.
Current State and Future Directions of Technology- based Ecological Momentary Assessments and Interventions for Major Depressive Disorder: Protocol for a Systematic Review.
Systematic Reviews, 7(1), BioMed Central.
December 2018.
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[CWL+20]
Ginevra Carbone, Matthew Wicker, Luca Laurenti, Andrea Patane, Luca Bortolussi and Guido Sanguinetti.
Robustness of Bayesian Neural Networks to Gradient-Based Attacks.
In 34th Conference on Neural Information Processing Systems (NeurIPS'20), Springer.
2020.
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[PLP+20]
Kyriakos Polymenakos, Luca Laurenti, Andrea Patane, Jan-Peter Calliess, Luca Cardelli, Marta Kwiatkowska, Alessandro Abate and Stephen Roberts.
Safety Guarantees for Iterative Predictions with Gaussian Processes.
In 59th Conference on Decision and Control (CDC'20), IEEE.
December 2020.
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[BPL+20]
Arno Blaas, Andrea Patane, Luca Laurenti, Luca Cardelli, Marta Kwiatkowska and Stephen Roberts.
Adversarial Robustness Guarantees for Classification with Gaussian Processes.
In 23rd International Conference on Artificial Intelligence and Statistics (AISTATS'20), PMLR.
August 2020.
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[WLPK20]
Matthew Wicker, Luca Laurenti, Andrea Patane and Marta Kwiatkowska.
Probabilistic Safety for Bayesian Neural Networks.
In 36th Conference on Uncertainty in Artificial Intelligence (UAI'20), PMLR.
August 2020.
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[GPG+20]
Shadi Ghiasi, Andrea Patane, Alberto Greco, Luca Laurenti, Enzo Pasquale Scilingo and Marta Kwiatkowska.
Gaussian Processes with Physiologically-Inspired Priors for Physical Arousal Recognition.
In 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society (EMBS'20).
July 2020.
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[CKLP19]
Luca Cardelli, Marta Kwiatkowska, Luca Laurenti and Andrea Patane.
Robustness Guarantees for Bayesian Inference with Gaussian Processes.
In Proc. Thirty-Third AAAI Conference on Artificial Intelligence (AAAI'19).
2019.
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[CKL+19a]
Luca Cardelli, Marta Kwiatkowska, Luca Laurenti, Nicola Paoletti, Andrea Patane, and Matthew Wicker.
Statistical Guarantees for the Robustness of Bayesian Neural Networks.
In Proc. International Joint Conference on Artificial Intelligence (IJCAI).
2019.
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[PGS+18]
Patane, A., Ghiasi, S., Scilingo, E.P., and Kwiatkowska, M.
Automated Recognition of Sleep Arousal using Multimodal and Personalized Deep Ensembles of Neural Networks.
In Proceedings of Computing in Cardiology 2018, IEEE.
2018.
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[ELP+18]
S. Eberz, G. Lovisotto, A. Patane, M. Kwiatkowska, V. Lenders and I. Martinovic.
When Your Fitness Tracker Betrays You: Quantifying the Predictability of Biometric Features Across Contexts.
In IEEE Symposium on Security and Privacy , IEEE.
2018.
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[RPL+18]
S. Rosa, A. Patane, X. Lu, and N. Trigoni.
CommonSense: Collaborative learning of scene semantics by robots and humans.
In 1st International Workshop on Internet of People, Assistive Robots and Things, Association for Computing Machinery.
2018.
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[PK18]
A. Patane and M. Kwiatkowska.
Calibrating the Classifier: Siamese Neural Network Architecture for End-to-End Arousal Recognition from ECG.
In Proc. Fourth International Conference on Machine Learning, Optimization, and Data Science, Springer.
2018.
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[KPP17]
M. Kwiatkowska, N. Paoletti, A. Patanè.
Closed-loop quantitative verification of rate-adaptive pacemakers.
In Proc. Oxford Computer Science Conference 2017.
2017.
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