Luca Laurenti

CoRR, 2024

2023

Physiologically-Informed Gaussian Processes for Interpretable Modelling of Psycho-Physiological States.

[BibT_eX]

[DOI]

Enzo Pasquale Scilingo

Alberto Greco

IEEE J. Biomed. Health Informatics, August, 2023

Formal Abstraction of General Stochastic Systems via Noise Partitioning.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2023

Promises of Deep Kernel Learning for Control Synthesis.

[BibT_eX]

[DOI]

Robert Reed

Frederik Baymler Mathiesen

IEEE Control. Syst. Lett., 2023

Safety Certification for Stochastic Systems via Neural Barrier Functions.

[BibT_eX]

[DOI]

Simeon C. Calvert

IEEE Control. Syst. Lett., 2023

Probabilistic Reach-Avoid for Bayesian Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2023

Unifying Safety Approaches for Stochastic Systems: From Barrier Functions to Uncertain Abstractions via Dynamic Programming.

[BibT_eX]

[DOI]

CoRR, 2023

Adversarial Robustness Certification for Bayesian Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2023

Individual Fairness in Bayesian Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2023

BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Distributionally Robust Strategy Synthesis for Switched Stochastic Systems.

[BibT_eX]

[DOI]

Proceedings of the 26th ACM International Conference on Hybrid Systems: Computation and Control, 2023

Interval Markov Decision Processes with Continuous Action-Spaces.

[BibT_eX]

[DOI]

Giannis Delimpaltadakis

Manuel Mazo Jr.

Frederik Baymler Mathiesen

Proceedings of the 26th ACM International Conference on Hybrid Systems: Computation and Control, 2023

Inner Approximations of Stochastic Programs for Data-Driven Stochastic Barrier Function Design.

[BibT_eX]

[DOI]

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

PID Control of Biochemical Reaction Networks.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2022

Adversarial Robustness Guarantees for Gaussian Processes.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

Formal Control Synthesis for Stochastic Neural Network Dynamic Models.

[BibT_eX]

[DOI]

Steven Adams

IEEE Control. Syst. Lett., 2022

On the Robustness of Bayesian Neural Networks to Adversarial Attacks.

[BibT_eX]

[DOI]

CoRR, 2022

Formal Analysis of the Sampling Behaviour of Stochastic Event-Triggered Control.

[BibT_eX]

[DOI]

Giannis Delimpaltadakis

Manuel Mazo Jr.

CoRR, 2022

Formal Verification of Unknown Dynamical Systems via Gaussian Process Regression.

[BibT_eX]

[DOI]

CoRR, 2022

Safety Guarantees for Neural Network Dynamic Systems via Stochastic Barrier Functions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Individual Fairness Guarantees for Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

Formal and Efficient Synthesis for Continuous-Time Linear Stochastic Hybrid Processes.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2021

A Language for Modeling and Optimizing Experimental Biological Protocols.

[BibT_eX]

[DOI]

Comput., 2021

Certification of iterative predictions in Bayesian neural networks.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Strategy synthesis for partially-known switched stochastic systems.

[BibT_eX]

[DOI]

Proceedings of the HSCC '21: 24th ACM International Conference on Hybrid Systems: Computation and Control, 2021

Synergistic Offline-Online Control Synthesis via Local Gaussian Process Regression.

[BibT_eX]

[DOI]

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Abstracting the Sampling Behaviour of Stochastic Linear Periodic Event-Triggered Control Systems.

[BibT_eX]

[DOI]

Giannis Delimpaltadakis

Manuel Mazo

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Bayesian Inference with Certifiable Adversarial Robustness.

[BibT_eX]

[DOI]

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Gradient-Free Adversarial Attacks for Bayesian Neural Networks.

[BibT_eX]

[DOI]

Matthew Yuan

Matthew Wicker

CoRR, 2020

Probabilistic Safety for Bayesian Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Robustness of Bayesian Neural Networks to Gradient-Based Attacks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Assessing Robustness of Text Classification through Maximal Safe Radius Computation.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Gaussian Processes with Physiologically-Inspired Priors for Physical Arousal Recognition.

[BibT_eX]

[DOI]

Enzo Pasquale Scilingo

Marta Z. Kwiatkowska

Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

Safety Guarantees for Iterative Predictions with Gaussian Processes.

[BibT_eX]

[DOI]

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Safety Verification of Unknown Dynamical Systems via Gaussian Process Regression.

[BibT_eX]

[DOI]

Proceedings of the 59th IEEE Conference on Decision and Control, 2020

Adversarial Robustness Guarantees for Classification with Gaussian Processes.

[BibT_eX]

[DOI]

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

2019

Central Limit Model Checking.

[BibT_eX]

[DOI]

ACM Trans. Comput. Log., 2019

Safety Guarantees for Planning Based on Iterative Gaussian Processes.

[BibT_eX]

[DOI]

CoRR, 2019

Robustness Quantification for Classification with Gaussian Processes.

[BibT_eX]

[DOI]

CoRR, 2019

Statistical Guarantees for the Robustness of Bayesian Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Efficiency through uncertainty: scalable formal synthesis for stochastic hybrid systems.

[BibT_eX]

[DOI]

Proceedings of the 22nd ACM International Conference on Hybrid Systems: Computation and Control, 2019

Robustness Guarantees for Bayesian Inference with Gaussian Processes.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Programming discrete distributions with chemical reaction networks.

[BibT_eX]

[DOI]

Nat. Comput., 2018

Experimental Biological Protocols with Formal Semantics.

[BibT_eX]

[DOI]

Proceedings of the Computational Methods in Systems Biology, 2018

2017

Reachability Computation for Switching Diffusions: Finite Abstractions with Certifiable and Tuneable Precision.

[BibT_eX]

[DOI]

Proceedings of the 20th International Conference on Hybrid Systems: Computation and Control, 2017

Syntax-Guided Optimal Synthesis for Chemical Reaction Networks.

[BibT_eX]

[DOI]

Proceedings of the Computer Aided Verification - 29th International Conference, 2017

2016

Stochastic analysis of Chemical Reaction Networks using Linear Noise Approximation.

[BibT_eX]

[DOI]

Biosyst., 2016

Approximation of Probabilistic Reachability for Chemical Reaction Networks Using the Linear Noise Approximation.

[BibT_eX]

[DOI]

Proceedings of the Quantitative Evaluation of Systems - 13th International Conference, 2016

A Stochastic Hybrid Approximation for Chemical Kinetics Based on the Linear Noise Approximation.

[BibT_eX]

[DOI]