3 citations · 3 across the 7 of their papers we have counts for
7 papers
Safe Reach Set Computation via Neural Barrier Certificates
Alessandro Abate, Sergiy Bogomolov, Alec Edwards +3
We present a novel technique for online safety verification of autonomous systems, which performs reachability analysis efficiently for both bounded and unbounded horizons by emplo…
Stability Analysis of Switched Linear Systems with Neural Lyapunov Functions
Virginie Debauche, Alec Edwards, Raphael M. Jungers +1
Neural-based, data-driven analysis and control of dynamical systems have been recently investigated and have shown great promise, e.g. for safety verification or stability analysis…
Fossil 2.0: Formal Certificate Synthesis for the Verification and Control of Dynamical Models
Alec Edwards, Andrea Peruffo, Alessandro Abate
This paper presents Fossil 2.0, a new major release of a software tool for the synthesis of certificates (e.g., Lyapunov and barrier functions) for dynamical systems modelled as or…
A General Framework for Verification and Control of Dynamical Models via Certificate Synthesis
Alec Edwards, Andrea Peruffo, Alessandro Abate
An emerging branch of control theory specialises in certificate learning, concerning the specification of a desired (possibly complex) system behaviour for an autonomous or control…
On the Trade-off Between Efficiency and Precision of Neural Abstraction
Alec Edwards, Mirco Giacobbe, Alessandro Abate
Neural abstractions have been recently introduced as formal approximations of complex, nonlinear dynamical models. They comprise a neural ODE and a certified upper bound on the err…
Neural Abstractions
Alessandro Abate, Alec Edwards, Mirco Giacobbe
We present a novel method for the safety verification of nonlinear dynamical models that uses neural networks to represent abstractions of their dynamics. Neural networks have exte…
Quantitative Verification with Neural Networks
Alessandro Abate, Alec Edwards, Mirco Giacobbe +2
We present a data-driven approach to the quantitative verification of probabilistic programs and stochastic dynamical models. Our approach leverages neural networks to compute tigh…