Towards Theoretical Understanding of Inverse Reinforcement Learning. - Alberto Maria Metelli; Filippo Lazzati; Marcello Restelli (ICML, 2023)

Offline Inverse RL: New Solution Concepts and Provably Efficient Algorithms. - Filippo Lazzati; Mirco Mutti; Alberto Maria Metelli (ICML, 2024)

How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach. - Filippo Lazzati; Mirco Mutti; Alberto Maria Metelli (NeurIPS, 2024)

How to Scale Inverse RL to Large State Spaces? A Provably Efficient Approach. - Filippo Lazzati; Mirco Mutti; Alberto Maria Metelli (CoRR, 2024)

Learning Utilities from Demonstrations in Markov Decision Processes. - Filippo Lazzati; Alberto Maria Metelli (CoRR, 2024)

On the Partial Identifiability in Reward Learning: Choosing the Best Reward. - Filippo Lazzati; Alberto Maria Metelli (CoRR, 2025)

Reward Compatibility: A Framework for Inverse RL. - Filippo Lazzati; Mirco Mutti; Alberto Maria Metelli (CoRR, 2025)