5 citations · 12 across the 9 of their papers we have counts for
4 papers · 1 filter
Scalable Verification of Neural Control Barrier Functions Using Linear Bound Propagation
Nikolaus Vertovec, Frederik Baymler Mathiesen, Thom Badings +2
Control barrier functions (CBFs) are a popular tool for safety certification of nonlinear dynamical control systems. Recently, CBFs represented as neural networks have shown great…
Certified Neural Approximations of Nonlinear Dynamics
Frederik Baymler Mathiesen, Nikolaus Vertovec, Francesco Fabiano +2
Neural networks hold great potential to act as approximate models of nonlinear dynamical systems, with the resulting neural approximations enabling verification and control of such…
SPoRt -- Safe Policy Ratio: Certified Training and Deployment of Task Policies in Model-Free RL
Jacques Cloete, Nikolaus Vertovec, Alessandro Abate
To apply reinforcement learning to safety-critical applications, we ought to provide safety guarantees during both policy training and deployment. In this work, we present theoreti…
Certified Approximate Reachability (CARe): Formal Error Bounds on Deep Learning of Reachable Sets
Prashant Solanki, Nikolaus Vertovec, Yannik Schnitzer +3
Recent approaches to leveraging deep learning for computing reachable sets of continuous-time dynamical systems have gained popularity over traditional level-set methods, as they o…