This manuscript presents the updated version of the Neural Network Verification (NNV) tool.
NNV is a formal verification software tool for deep learning models and cyber-physical …

This report presents the results of a friendly competition for formal verification of continuous
and hybrid systems with artificial intelligence (AI) components. Specifically, machine …

This interactive tutorial describes state-of-the-art methods for formally verifying neural
networks and their usage within safety-critical cyber-physical systems (CPS). The inclusion …

Abstract Machine Learning approaches have been successfully used for the creation of high-
performance control components of cyber-physical systems, where the control dynamics …

In this case study, we have explored the use of a neural network model checker to analyze
the safety characteristics of a neural network trained using reinforcement learning to …

Abstract Machine Learning approaches have been successfully used for the creation of high-
performance control components of cyber–physical systems, where the control dynamics …

Abstract Benchmark Proposal: Neural Network Control Systems (NNCS) play critical roles in
autonomy. However, verifying their correctness is a substantial challenge. In this paper, we …

While Artificial Intelligence (AI) has become an important asset in many areas of science and
technology, safety is often not treated as important as required for aviation. Neglecting safety …

Neural networks have emerged as powerful tools across various domains, exhibiting
remarkable empirical performance that motivated their widespread adoption in safety-critical …

Given the safety-critical functions of autonomous cyber-physical systems (CPS) across
diverse domains, testing these systems is essential. While conventional software and …