Towards Hierarchical Task Decomposition using Deep Reinforcement Learning for Pick and Place Subtasks. - Luca Marzari; Ameya Pore; Diego Dall'Alba; Gerardo Aragon-Camarasa; Alessandro Farinelli; Paolo Fiorini (ICAR, 2021)

Curriculum learning for safe mapless navigation. - Luca Marzari; Davide Corsi; Enrico Marchesini; Alessandro Farinelli (SAC, 2022)

Scaling #DNN-Verification Tools with Efficient Bound Propagation and Parallel Computing (regular paper). - Luca Marzari; Gabriele Roncolato; Alessandro Farinelli (AIRO@AI*IA, 2023)

Safe Deep Reinforcement Learning by Verifying Task-Level Properties. - Enrico Marchesini; Luca Marzari; Alessandro Farinelli; Christopher Amato (AAMAS, 2023)

Online Safety Property Collection and Refinement for Safe Deep Reinforcement Learning in Mapless Navigation. - Luca Marzari; Enrico Marchesini; Alessandro Farinelli (ICRA, 2023)

The #DNN-Verification Problem: Counting Unsafe Inputs for Deep Neural Networks. - Luca Marzari; Davide Corsi; Ferdinando Cicalese; Alessandro Farinelli (IJCAI, 2023)

Constrained Reinforcement Learning and Formal Verification for Safe Colonoscopy Navigation. - Davide Corsi; Luca Marzari; Ameya Pore; Alessandro Farinelli; Alicia Casals; Paolo Fiorini; Diego Dall'Alba (IROS, 2023)

Safe and Efficient Reinforcement Learning for Environmental Monitoring. - Federico Bianchi 002; Davide Corsi; Luca Marzari; Daniele Meli; Francesco Trotti; Maddalena Zuccotto; Alberto Castellini; Alessandro Farinelli (Ital-IA, 2023)

Verifying Learning-Based Robotic Navigation Systems. - Guy Amir; Davide Corsi; Raz Yerushalmi; Luca Marzari; David Harel; Alessandro Farinelli; Guy Katz (TACAS (1), 2023)

Scaling #DNN-Verification Tools with Efficient Bound Propagation and Parallel Computing. - Luca Marzari; Gabriele Roncolato; Alessandro Farinelli (CoRR, 2023)

Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees. - Luca Marzari; Davide Corsi; Enrico Marchesini; Alessandro Farinelli; Ferdinando Cicalese (AAAI, 2024)

Rigorous Probabilistic Guarantees for Robust Counterfactual Explanations. - Luca Marzari; Francesco Leofante; Ferdinando Cicalese; Alessandro Farinelli (ECAI, 2024)

Developing safe and explainable autonomous agents: from simulation to the real world. - Federico Bianchi 002; Alberto Castellini; Alessandro Farinelli; Luca Marzari; Daniele Meli; Francesco Trotti; Celeste Veronese (Ital-IA, 2024)

ModelVerification.jl: A Comprehensive Toolbox for Formally Verifying Deep Neural Networks. - Tianhao Wei; Hanjiang Hu; Luca Marzari; Kai S. Yun; Peizhi Niu; Xusheng Luo; Changliu Liu (CAV (2), 2025)

Improving Policy Optimization via ε-Retrain. - Luca Marzari; Priya L. Donti; Changliu Liu; Enrico Marchesini (AAMAS, 2025)

RobustX: Robust Counterfactual Explanations Made Easy. - Junqi Jiang; Luca Marzari; Aaryan Purohit; Francesco Leofante (CoRR, 2025)

Advancing Neural Network Verification through Hierarchical Safety Abstract Interpretation. - Luca Marzari; Isabella Mastroeni; Alessandro Farinelli (CoRR, 2025)

Probabilistically Tightened Linear Relaxation-based Perturbation Analysis for Neural Network Verification. - Luca Marzari; Ferdinando Cicalese; Alessandro Farinelli (CoRR, 2025)

Formal Verification of Variational Quantum Circuits. - Nicola Assolini; Luca Marzari; Isabella Mastroeni; Alessandra Di Pierro (CoRR, 2025)

Designing Control Barrier Function via Probabilistic Enumeration for Safe Reinforcement Learning Navigation. - Luca Marzari; Francesco Trotti; Enrico Marchesini; Alessandro Farinelli (IEEE Robotics Autom. Lett., 2025)