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 …

We present VMT-LIB, a language for the representation of verification problems of linear-
time temporal properties on infinite-state symbolic transition systems. VMT-LIB is an …

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 …

Quantitative notions of bisimulation are well-known tools for the minimization of dynamical
models such as Markov chains and ordinary differential equations (ODEs). In forward …

Dynamical models are a mathematical tool for representing, understanding, and analysing
complex systems that are ubiquitous across science and engineering. Complexity and …

We propose to simulate chemical reaction networks with the deterministic semantics
abstractly, without any precise knowledge on the initial concentrations. For this, the …

An important topic of research in formal verification is the safety verification of hybrid
systems. Hybrid systems include both discrete and continuous dynamics, and are used to …

This thesis deals with several abstractions that create a discrete transition system from an
input continuous-time system with dynamics given by a system of autonomous ODE that are …