This report summarizes the 4th International Verification of Neural Networks Competition
(VNN-COMP 2023), held as a part of the 6th Workshop on Formal Methods for ML-Enabled …

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 …

Neural networks (NNs) are increasingly applied in safety-critical systems such as
autonomous vehicles. However, they are fragile and are often ill-behaved. Consequently …

Malware, or software designed with harmful intent, is an ever-evolving threat that can have
drastic effects on both individuals and institutions. Neural network malware classification …

Neural Ordinary Differential Equations (NODEs) are a novel neural architecture, built around
initial value problems with learned dynamics which are solved during inference. Thought to …

The exploding research interest for neural networks in modeling nonlinear dynamical
systems is largely explained by the networks' capacity to model complex input-output …

Recent progress in autonomous vehicle technology has led to the development of accurate
and efficient tools for ensuring safety, which is crucial for verifying the reliability and security …

This report summarizes the 5th International Verification of Neural Networks Competition
(VNN-COMP 2024), held as a part of the 7th International Symposium on AI Verification …

Recent advances in autonomous vehicles have encouraged researchers to provide
accurate and efficient safety verification tools. Reachability analysis is one way to provide …