4 papers
A Survey on the Verification of Reinforcement Learning Policies
Luca Marzari, Ezio Bartocci, Enrico Marchesini
Reinforcement learning (RL) is increasingly applied in complex, safety-critical domains, yet the lack of rigorous behavioral guarantees for neural network-based policies remains a…
Probabilistically Tightened Linear Relaxation-based Perturbation Analysis for Neural Network Verification
Luca Marzari, Ferdinando Cicalese, Alessandro Farinelli
We present robabilistically ightened near elaxation-based erturbation nalysis (), a nove…
Formal Verification of Variational Quantum Circuits
Nicola Assolini, Luca Marzari, Isabella Mastroeni +1
Variational quantum circuits (VQCs) are a central component of many quantum machine learning algorithms, offering a hybrid quantum-classical framework that, under certain aspects,…
Advancing Neural Network Verification through Hierarchical Safety Abstract Interpretation
Luca Marzari, Isabella Mastroeni, Alessandro Farinelli
Traditional methods for formal verification (FV) of deep neural networks (DNNs) are constrained by a binary encoding of safety properties, where a model is classified as either saf…