Mathieu Reymond

28 papers A* 1A 7Journal 19Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	CoPeP: Benchmarking Continual Pretraining for Protein Language Models. CoRR Darshan Patil, Pranshu Malviya, Mathieu Reymond, Quentin Fournier, Sarath Chandar
2026	J	`jnl`	MMAI Gym for Science: Training Liquid Foundation Models for Drug Discovery. CoRR Maksim Kuznetsov, Zulfat Miftahutdinov, Rim Shayakhmetov, Mikolaj Mizera, Roman Schutski, Bogdan Zagribelnyy, Ivan Ilin, Nikita Bondarev, Thomas MacDougall, Mathieu Reymond, Mihir Bafna, Kaeli Kaymak-Loveless, Eugene Babin, Maxim Malkov, Mathias Lechner, Ramin M. Hasani, Alexander Amini, Vladimir Aladinskiy, Alex Aliper, Alex Zhavoronkov
2026	J	`jnl`	Squeezing More from the Stream : Learning Representation Online for Streaming Reinforcement Learning. CoRR Nilaksh, Antoine Clavaud, Mathieu Reymond, François Rivest, Sarath Chandar
2025	A*	`conf`	A Generalist Hanabi Agent. ICLR Arjun Vaithilingam Sudhakar, Hadi Nekoei, Mathieu Reymond, Miao Liu, Janarthanan Rajendran, Sarath Chandar
2025	J	`jnl`	A Generalist Hanabi Agent. CoRR Arjun Vaithilingam Sudhakar, Hadi Nekoei, Mathieu Reymond, Miao Liu, Janarthanan Rajendran, Sarath Chandar
2025	J	`jnl`	CrystalGym: A New Benchmark for Materials Discovery Using Reinforcement Learning. CoRR Prashant Govindarajan, Mathieu Reymond, Antoine Clavaud, Mariano Phielipp, Santiago Miret, Sarath Chandar
2025	A	`conf`	Divide and Conquer: Provably Unveiling the Pareto Front with Multi-Objective Reinforcement Learning. AAMAS Willem Röpke, Mathieu Reymond, Patrick Mannion, Diederik M. Roijers, Ann Nowé, Roxana Radulescu
2025	J	`jnl`	GRPO-λ: Credit Assignment improves LLM Reasoning. CoRR Prasanna Parthasarathi, Mathieu Reymond, Boxing Chen, Yufei Cui, Sarath Chandar
2025	J	`jnl`	Just-in-time Episodic Feedback Hinter: Leveraging Offline Knowledge to Improve LLM Agents Adaptation. CoRR Hadi Nekoei, Aman Jaiswal, Patrice Béchard, Oleh Shliazhko, Orlando Marquez Ayala, Mathieu Reymond, Massimo Caccia, Alexandre Drouin, Sarath Chandar, Alexandre Lacoste
2024	J	`jnl`	Divide and Conquer: Provably Unveiling the Pareto Front with Multi-Objective Reinforcement Learning. CoRR Willem Röpke, Mathieu Reymond, Patrick Mannion, Diederik M. Roijers, Ann Nowé, Roxana Radulescu
2024	J	`jnl`	Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning. Expert Syst. Appl. Mathieu Reymond, Conor F. Hayes, Lander Willem, Roxana Radulescu, Steven Abrams, Diederik M. Roijers, Enda Howley, Patrick Mannion, Niel Hens, Ann Nowé, Pieter Libin
2024	A	`conf`	Interactively Learning the User's Utility for Best-Arm Identification in Multi-Objective Multi-Armed Bandits. AAMAS Mathieu Reymond, Eugenio Bargiacchi, Diederik M. Roijers, Ann Nowé
2023	A	`conf`	A Brief Guide to Multi-Objective Reinforcement Learning and Planning. AAMAS Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
2023	J	`jnl`	Actor-critic multi-objective reinforcement learning for non-linear utility functions. Auton. Agents Multi Agent Syst. Mathieu Reymond, Conor F. Hayes, Denis Steckelmacher, Diederik M. Roijers, Ann Nowé
2023	J	`jnl`	Local Advantage Networks for Multi-Agent Reinforcement Learning in Dec-POMDPs. Trans. Mach. Learn. Res. Raphaël Avalos, Mathieu Reymond, Ann Nowé, Diederik M. Roijers
2023	J	`jnl`	Monte Carlo tree search algorithms for risk-aware and multi-objective reinforcement learning. Auton. Agents Multi Agent Syst. Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
2022	J	`jnl`	A practical guide to multi-objective reinforcement learning and planning. Auton. Agents Multi Agent Syst. Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
2022	J	`jnl`	Exploring the Pareto front of multi-objective COVID-19 mitigation policies using reinforcement learning. CoRR Mathieu Reymond, Conor F. Hayes, Lander Willem, Roxana Radulescu, Steven Abrams, Diederik M. Roijers, Enda Howley, Patrick Mannion, Niel Hens, Ann Nowé, Pieter Libin
2022	A	`conf`	Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning. AAMAS Raphaël Avalos, Mathieu Reymond, Ann Nowé, Diederik M. Roijers
2022	J	`jnl`	Monte Carlo Tree Search Algorithms for Risk-Aware and Multi-Objective Reinforcement Learning. CoRR Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
2022	A	`conf`	Near On-Policy Experience Sampling in Multi-Objective Reinforcement Learning. AAMAS Shang Wang, Mathieu Reymond, Athirai A. Irissappane, Diederik M. Roijers
2022	A	`conf`	Pareto Conditioned Networks. AAMAS Mathieu Reymond, Eugenio Bargiacchi, Ann Nowé
2022	J	`jnl`	Pareto Conditioned Networks. CoRR Mathieu Reymond, Eugenio Bargiacchi, Ann Nowé
2021	J	`jnl`	A Practical Guide to Multi-Objective Reinforcement Learning and Planning. CoRR Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
2021	A	`conf`	Distributional Monte Carlo Tree Search for Risk-Aware and Multi-Objective Reinforcement Learning. AAMAS Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
2021	J	`jnl`	Local Advantage Networks for Cooperative Multi-Agent Reinforcement Learning. CoRR Raphaël Avalos, Mathieu Reymond, Ann Nowé, Diederik M. Roijers
2021	J	`jnl`	Risk Aware and Multi-Objective Decision Making with Distributional Monte Carlo Tree Search. CoRR Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley, Patrick Mannion
2020	—	`conf`	Interactive Multi-objective Reinforcement Learning in Multi-armed Bandits with Gaussian Process Utility Models. ECML/PKDD (3) Diederik M. Roijers, Luisa M. Zintgraf, Pieter Libin, Mathieu Reymond, Eugenio Bargiacchi, Ann Nowé