Gradient-Aware Model-Based Policy Search. - Pierluca D'Oro; Alberto Maria Metelli; Andrea Tirinzoni; Matteo Papini; Marcello Restelli (AAAI, 2020)

How to Learn a Useful Critic? Model-based Action-Gradient-Estimator Policy Optimization. - Pierluca D'Oro; Wojciech Jaskowski (NeurIPS, 2020)

Real-time Classification from Short Event-Camera Streams using Input-filtering Neural ODEs. - Giorgio Giannone; Asha Anoosheh; Alessio Quaglino; Pierluca D'Oro; Marco Gallieri; Jonathan Masci (CoRR, 2020)

Policy Optimization as Online Learning with Mediator Feedback. - Alberto Maria Metelli; Matteo Papini; Pierluca D'Oro; Marcello Restelli (AAAI, 2021)

The Primacy Bias in Deep Reinforcement Learning. - Evgenii Nikishin; Max Schwarzer; Pierluca D'Oro; Pierre-Luc Bacon; Aaron C. Courville (ICML, 2022)

Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier. - Pierluca D'Oro; Max Schwarzer; Evgenii Nikishin; Pierre-Luc Bacon; Marc G. Bellemare; Aaron C. Courville (ICLR, 2023)

Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control. - Nate Rahn; Pierluca D'Oro; Harley Wiltzer; Pierre-Luc Bacon; Marc G. Bellemare (NeurIPS, 2023)

Motif: Intrinsic Motivation from Artificial Intelligence Feedback. - Martin Klissarov; Pierluca D'Oro; Shagun Sodhani; Roberta Raileanu; Pierre-Luc Bacon; Pascal Vincent; Amy Zhang 001; Mikael Henaff (ICLR, 2024)

The Curse of Diversity in Ensemble-Based Exploration. - Zhixuan Lin; Pierluca D'Oro; Evgenii Nikishin; Aaron C. Courville (ICLR, 2024)

Do Transformer World Models Give Better Policy Gradients? - Michel Ma; Tianwei Ni; Clement Gehring; Pierluca D'Oro; Pierre-Luc Bacon (ICML, 2024)

Maxwell's Demon at Work: Efficient Pruning by Leveraging Saturation of Neurons. - Simon Dufort-Labbé; Pierluca D'Oro; Evgenii Nikishin; Razvan Pascanu; Pierre-Luc Bacon; Aristide Baratin (CoRR, 2024)

Controlling Large Language Model Agents with Entropic Activation Steering. - Nate Rahn; Pierluca D'Oro; Marc G. Bellemare (CoRR, 2024)

Towards General-Purpose Model-Free Reinforcement Learning. - Scott Fujimoto; Pierluca D'Oro; Amy Zhang 001; Yuandong Tian; Michael Rabbat (ICLR, 2025)

MaestroMotif: Skill Design from Artificial Intelligence Feedback. - Martin Klissarov; Mikael Henaff; Roberta Raileanu; Shagun Sodhani; Pascal Vincent; Amy Zhang 001; Pierre-Luc Bacon; Doina Precup; Marlos C. Machado; Pierluca D'Oro (ICLR, 2025)

Maxwell's Demon at Work: Efficient Pruning by Leveraging Saturation of Neurons. - Simon Dufort-Labbé; Pierluca D'Oro; Evgenii Nikishin; Irina Rish; Pierre-Luc Bacon; Razvan Pascanu; Aristide Baratin (Trans. Mach. Learn. Res., 2025)

Mol-MoE: Training Preference-Guided Routers for Molecule Generation. - Diego Calanzone; Pierluca D'Oro; Pierre-Luc Bacon (CoRR, 2025)

ADEPTS: A Capability Framework for Human-Centered Agent Design. - Pierluca D'Oro; Caley Drooff; Joy Chen; Joseph Tighe (CoRR, 2025)