Andrea Patanè

According to our database1, Andrea Patanè authored at least 24 papers between 2015 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2021
Bayesian Inference with Certifiable Adversarial Robustness.
CoRR, 2021

2020
Probabilistic Safety for Bayesian Neural Networks.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Robustness of Bayesian Neural Networks to Gradient-Based Attacks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Gaussian Processes with Physiologically-Inspired Priors for Physical Arousal Recognition.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

Safety Guarantees for Iterative Predictions with Gaussian Processes.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Adversarial Robustness Guarantees for Classification with Gaussian Processes.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Semantic Place Understanding for Human-Robot Coexistence - Toward Intelligent Workplaces.
IEEE Trans. Hum. Mach. Syst., 2019

Safety Guarantees for Planning Based on Iterative Gaussian Processes.
CoRR, 2019

Robustness Quantification for Classification with Gaussian Processes.
CoRR, 2019

Multi-objective optimization of genome-scale metabolic models: the case of ethanol production.
Ann. Oper. Res., 2019

Statistical Guarantees for the Robustness of Bayesian Neural Networks.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Robustness Guarantees for Bayesian Inference with Gaussian Processes.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Closed-Loop Quantitative Verification of Rate-Adaptive Pacemakers.
ACM Trans. Cyber Phys. Syst., 2018

Enhancing quantum efficiency of thin-film silicon solar cells by Pareto optimality.
J. Glob. Optim., 2018

When Your Fitness Tracker Betrays You: Quantifying the Predictability of Biometric Features Across Contexts.
Proceedings of the 2018 IEEE Symposium on Security and Privacy, 2018

Calibrating the Classifier: Siamese Neural Network Architecture for End-to-End Arousal Recognition from ECG.
Proceedings of the Machine Learning, Optimization, and Data Science, 2018

CommonSense: Collaborative learning of scene semantics by robots and humans.
Proceedings of the 1st International Workshop on Internet of People, 2018

Automated Recognition of Sleep Arousal Using Multimodal and Personalized Deep Ensembles of Neural Networks.
Proceedings of the Computing in Cardiology, 2018

2017
Multi-objective optimization and analysis for the design space exploration of analog circuits and solar cells.
Eng. Appl. Artif. Intell., 2017

Broken Hearted: How To Attack ECG Biometrics.
Proceedings of the 24th Annual Network and Distributed System Security Symposium, 2017

2016
Metabolic Circuit Design Automation by Multi-objective BioCAD.
Proceedings of the Machine Learning, Optimization, and Big Data, 2016

2015
Pareto Optimal Design for Synthetic Biology.
IEEE Trans. Biomed. Circuits Syst., 2015

Synthesising Robust and Optimal Parameters for Cardiac Pacemakers Using Symbolic and Evolutionary Computation Techniques.
Proceedings of the Hybrid Systems Biology - Fourth International Workshop, 2015

Hardware-in-the-loop simulation and energy optimization of cardiac pacemakers.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015


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