6 papers
Quantitative Monitoring of Signal First-Order Logic
Marek Chalupa, Thomas A. Henzinger, N. Ege Saraç +1
Runtime monitoring checks, during execution, whether a partial signal produced by a hybrid system satisfies its specification. Signal First-Order Logic (SFO) offers expressive real…
Logic Gate Neural Networks are Good for Verification
Fabian Kresse, Emily Yu, Christoph H. Lampert +1
Learning-based systems are increasingly deployed across various domains, yet the complexity of traditional neural networks poses significant challenges for formal verification. Unl…
Scalable Interconnect Learning in Boolean Networks
Fabian Kresse, Emily Yu, Christoph H. Lampert
Learned Differentiable Boolean Logic Networks (DBNs) already deliver efficient inference on resource-constrained hardware. We extend them with a trainable, differentiable interconn…
Formal Verification of Neural Certificates Done Dynamically
Thomas A. Henzinger, Konstantin Kueffner, Emily Yu
Neural certificates have emerged as a powerful tool in cyber-physical systems control, providing witnesses of correctness. These certificates, such as barrier functions, often lear…
Predictive Monitoring of Black-Box Dynamical Systems
Thomas A. Henzinger, Fabian Kresse, Kaushik Mallik +2
We study the problem of predictive runtime monitoring of black-box dynamical systems with quantitative safety properties. The black-box setting stipulates that the exact semantics…
Neural Control and Certificate Repair via Runtime Monitoring
Emily Yu, ÄorÄe ŽikeliÄ, Thomas A. Henzinger
Learning-based methods provide a promising approach to solving highly non-linear control tasks that are often challenging for classical control methods. To ensure the satisfaction…