Rachelson, Emmanuel

12 publications

NeurIPS 2025 A Markov Decision Process for Variable Selection in Branch & Bound Paul Strang, Zacharie Ales, Côme Bissuel, Olivier Juan, Safia Kedad-Sidhoum, Emmanuel Rachelson

NeurIPS 2024 Exploration by Learning Diverse Skills Through Successor State Representations Paul-Antoine Le Tolguenec, Yann Besse, Florent Teichteil-Konigsbuch, Dennis G. Wilson, Emmanuel Rachelson

TMLR 2024 Learning State Reachability as a Graph in Translation Invariant Goal-Based Reinforcement Learning Tasks Hedwin Bonnavaud, Alexandre Albore, Emmanuel Rachelson

NeurIPS 2024 Time-Constrained Robust MDPs Adil Zouitine, David Bertoin, Pierre Clavier, Matthieu Geist, Emmanuel Rachelson

ICML 2022 Large Batch Experience Replay Thibault Lahire, Matthieu Geist, Emmanuel Rachelson

ICLR 2022 Local Feature Swapping for Generalization in Reinforcement Learning David Bertoin, Emmanuel Rachelson

NeurIPS 2022 Look Where You Look! Saliency-Guided Q-Networks for Generalization in Visual Reinforcement Learning David Bertoin, Adil Zouitine, Mehdi Zouitine, Emmanuel Rachelson

CoLLAs 2022 Neural Distillation as a State Representation Bottleneck in Reinforcement Learning Valentin Guillet, Dennis George Wilson, Emmanuel Rachelson

AutoML 2022 When, Where, and How to Add New Neurons to ANNs Kaitlin Maile, Emmanuel Rachelson, Hervé Luga, Dennis George Wilson

AAAI 2021 Lipschitz Lifelong Reinforcement Learning Erwan Lecarpentier, David Abel, Kavosh Asadi, Yuu Jinnai, Emmanuel Rachelson, Michael L. Littman

NeurIPS 2019 Non-Stationary Markov Decision Processes, a Worst-Case Approach Using Model-Based Reinforcement Learning Erwan Lecarpentier, Emmanuel Rachelson

IJCAI 2018 Open Loop Execution of Tree-Search Algorithms Erwan Lecarpentier, Guillaume Infantes, Charles Lesire, Emmanuel Rachelson