Vincent François-Lavet

53 papers A* 6Misc 1Journal 34Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	CICADA: A Workflow Guidance for Causal Machine Learning in Precision Medicine. BIOSTEC (3) Louk van Remmerden, Ilona Baranska, Ameet R. Jagesar, Eline Tankink-Kooijmans, Jitka Pokladníková, Paulina Wisniewska, Daniela Fialová, Emiel Hoogendijk, Karlijn Joling, Katarzyna Szczerbinska, Vincent François-Lavet, Shujian Yu, Mark Hoogendoorn, Hein van Hout
2025	J	`jnl`	Guiding Skill Discovery with Foundation Models. CoRR Zhao Yang, Thomas M. Moerland, Mike Preuss, Aske Plaat, Vincent François-Lavet, Edward S. Hu
2025	J	`jnl`	Hadamax Encoding: Elevating Performance in Model-Free Atari. CoRR Jacob E. Kooi, Zhao Yang, Vincent François-Lavet
2025	J	`jnl`	Learning Abstract World Models with a Group-Structured Latent Space. CoRR Thomas Delliaux, Nguyen-Khanh Vu, Vincent François-Lavet, Elise van der Pol, Emmanuel Rachelson
2025	J	`jnl`	Learning Task-Aware Abstract Representations for Meta-Reinforcement Learning. Trans. Mach. Learn. Res. Louk van Remmerden, Zhao Yang, Shujian Yu, Mark Hoogendoorn, Vincent François-Lavet
2025	J	`jnl`	Leveraging weights signals - Predicting and improving generalizability in reinforcement learning. CoRR Olivier Moulin, Vincent François-Lavet, Paul W. G. Elbers, Mark Hoogendoorn
2025	J	`jnl`	Multi-layer Abstraction for Nested Generation of Options (MANGO) in Hierarchical Reinforcement Learning. CoRR Alessio Arcudi, Davide Sartor, Alberto Sinigaglia, Vincent François-Lavet, Gian Antonio Susto
2025	J	`jnl`	Novel RL approach for efficient Elevator Group Control Systems. CoRR Nathan Vaartjes, Vincent François-Lavet
2024	J	`jnl`	Comparative performance of intensive care mortality prediction models based on manually curated versus automatically extracted electronic health record data. Int. J. Medical Informatics Ameet R. Jagesar, Martijn Otten, Tariq A. Dam, Laurens Biesheuvel, Dave A. Dongelmans, Sylvia Brinkman, Patrick J. Thoral, Vincent François-Lavet, Armand R. J. Girbes, Nicolette de Keizer, Harm-Jan de Grooth, Paul W. G. Elbers
2024	J	`jnl`	Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey. IEEE Trans. Neural Networks Learn. Syst. Amjad Yousef Majid, Serge Saaybi, Vincent François-Lavet, R. Venkatesha Prasad, Chris J. M. Verhoeven
2024	J	`jnl`	Guideline-informed reinforcement learning for mechanical ventilation in critical care. Artif. Intell. Medicine Floris den Hengst, Martijn Otten, Paul W. G. Elbers, Frank van Harmelen, Vincent François-Lavet, Mark Hoogendoorn
2024	J	`jnl`	Latent Assistance Networks: Rediscovering Hyperbolic Tangents in RL. CoRR Jacob E. Kooi, Mark Hoogendoorn, Vincent François-Lavet
2024	J	`jnl`	Leveraging Knowledge Graph-Based Human-Like Memory Systems to Solve Partially Observable Markov Decision Processes. CoRR Taewoon Kim, Vincent François-Lavet, Michael Cochez
2023	A*	`conf`	A Machine with Short-Term, Episodic, and Semantic Memory Systems. AAAI Taewoon Kim, Michael Cochez, Vincent François-Lavet, Mark A. Neerincx, Piek Vossen
2023	—	`conf`	A Meta-Reinforcement Learning Algorithm for Causal Discovery. CLeaR Andreas W. M. Sauter, Erman Acar, Vincent François-Lavet
2023	—	`conf`	Disentangled (Un)Controllable Features. SSCI Jacob E. Kooi, Mark Hoogendoorn, Vincent François-Lavet
2023	—	`conf`	Improving Generalization in Reinforcement Learning Through Forked Agents. IEA/AIE (2) Olivier Moulin, Vincent François-Lavet, Paul W. G. Elbers, Mark Hoogendoorn
2022	J	`jnl`	A Machine With Human-Like Memory Systems. CoRR Taewoon Kim, Michael Cochez, Vincent François-Lavet, Mark A. Neerincx, Piek Vossen
2022	J	`jnl`	A Machine with Short-Term, Episodic, and Semantic Memory Systems. CoRR Taewoon Kim, Michael Cochez, Vincent François-Lavet, Mark A. Neerincx, Piek Vossen
2022	J	`jnl`	A Meta-Reinforcement Learning Algorithm for Causal Discovery. CoRR Andreas Sauter, Erman Acar, Vincent François-Lavet
2022	J	`jnl`	Disentangled (Un)Controllable Features. CoRR Jacob E. Kooi, Mark Hoogendoorn, Vincent François-Lavet
2022	J	`jnl`	Improving adaptability to new environments and removing catastrophic forgetting in Reinforcement Learning by using an eco-system of agents. CoRR Olivier Moulin, Vincent François-Lavet, Paul W. G. Elbers, Mark Hoogendoorn
2022	J	`jnl`	Improving generalization in reinforcement learning through forked agents. CoRR Olivier Moulin, Vincent François-Lavet, Mark Hoogendoorn
2022	—	`conf`	Improving generalization to new environments and removing catastrophic forgetting in Reinforcement Learning by using an eco-system of agents. WI/IAT Olivier Moulin, Vincent François-Lavet, Paul W. G. Elbers, Mark Hoogendoorn
2022	J	`jnl`	Planning for potential: efficient safe reinforcement learning. Mach. Learn. Floris den Hengst, Vincent François-Lavet, Mark Hoogendoorn, Frank van Harmelen
2022	A*	`conf`	Reinforcement Learning with Option Machines. IJCAI Floris den Hengst, Vincent François-Lavet, Mark Hoogendoorn, Frank van Harmelen
2021	J	`jnl`	Component Transfer Learning for Deep RL Based on Abstract Representations. CoRR Geoffrey van Driessel, Vincent François-Lavet
2021	J	`jnl`	Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey. CoRR Amjad Yousef Majid, Serge Saaybi, Tomas van Rietbergen, Vincent François-Lavet, R. Venkatesha Prasad, Chris J. M. Verhoeven
2021	J	`jnl`	Domain Adversarial Reinforcement Learning. CoRR Bonnie Li, Vincent François-Lavet, Thang Doan, Joelle Pineau
2021	—	`conf`	Understanding Capacity Saturation in Incremental Learning. Canadian AI Shenyang Huang, Vincent François-Lavet, Guillaume Rabusseau
2020	A*	`conf`	Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks. IJCAI Maxime Wabartha, Audrey Durand, Vincent François-Lavet, Joelle Pineau
2020	A*	`conf`	Novelty Search in Representational Space for Sample Efficient Exploration. NeurIPS Ruo Yu Tao, Vincent François-Lavet, Joelle Pineau
2020	J	`jnl`	Novelty Search in representational space for sample efficient exploration. CoRR Ruo Yu Tao, Vincent François-Lavet, Joelle Pineau
2020	A*	`conf`	On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract). IJCAI Vincent François-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst, Raphael Fonteneau
2020	J	`jnl`	RandomNet: Towards Fully Automatic Neural Architecture Design for Multimodal Learning. CoRR Stefano Alletto, Shenyang Huang, Vincent François-Lavet, Yohei Nakata, Guillaume Rabusseau
2019	A*	`conf`	Combined Reinforcement Learning via Abstract Representations. AAAI Vincent François-Lavet, Yoshua Bengio, Doina Precup, Joelle Pineau
2019	J	`jnl`	Neural Architecture Search for Class-incremental Learning. CoRR Shenyang Huang, Vincent François-Lavet, Guillaume Rabusseau
2019	J	`jnl`	On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability. J. Artif. Intell. Res. Vincent François-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst, Raphael Fonteneau
2018	J	`jnl`	An Introduction to Deep Reinforcement Learning. CoRR Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau
2018	J	`jnl`	An Introduction to Deep Reinforcement Learning. Found. Trends Mach. Learn. Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau
2018	J	`jnl`	Combined Reinforcement Learning via Abstract Representations. CoRR Vincent François-Lavet, Yoshua Bengio, Doina Precup, Joelle Pineau
2018	Misc	`conf`	Reward Estimation for Variance Reduction in Deep Reinforcement Learning. CoRL Joshua Romoff, Peter Henderson, Alexandre Piché, Vincent François-Lavet, Joelle Pineau
2018	—	`conf`	Reward Estimation for Variance Reduction in Deep Reinforcement Learning. ICLR (Workshop) Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau
2018	J	`jnl`	Reward Estimation for Variance Reduction in Deep Reinforcement Learning. CoRR Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau
2017	—	`conf`	Approximate Bayes Optimal Policy Search using Neural Networks. ICAART (2) Michael Castronovo, Vincent François-Lavet, Raphaël Fonteneau, Damien Ernst, Adrien Couëtoux
2017	—	`—`	Contributions to deep reinforcement learning and its applications in smartgrids. Vincent François-Lavet
2017	J	`jnl`	On overfitting and asymptotic bias in batch reinforcement learning with partial observability. CoRR Vincent François-Lavet, Damien Ernst, Raphael Fonteneau
2015	J	`jnl`	How to Discount Deep Reinforcement Learning: Towards New Dynamic Strategies. CoRR Vincent François-Lavet, Raphaël Fonteneau, Damien Ernst
2015	—	`conf`	Imitative Learning for Online Planning in Microgrids. DARE Samy Aittahar, Vincent François-Lavet, Stefan Lodeweyckx, Damien Ernst, Raphaël Fonteneau
2014	—	`conf`	Simple Connectome Inference from Partial Correlation Statistics in Calcium Imaging. Neural Connectomics Antonio Sutera, Arnaud Joly, Vincent François-Lavet, Zixiao Aaron Qiu, Gilles Louppe, Damien Ernst, Pierre Geurts
2014	J	`jnl`	Simple connectome inference from partial correlation statistics in calcium imaging. CoRR Antonio Sutera, Arnaud Joly, Vincent François-Lavet, Zixiao Aaron Qiu, Gilles Louppe, Damien Ernst, Pierre Geurts
2014	—	`conf`	Using approximate dynamic programming for estimating the revenues of a hydrogen-based high-capacity storage device. ADPRL Vincent François-Lavet, Raphaël Fonteneau, Damien Ernst
2013	J	`jnl`	An energy-based variational model of ferromagnetic hysteresis for finite element computations. J. Comput. Appl. Math. Vincent François-Lavet, François Henrotte, Laurent Stainier, Ludovic Noels, Christophe Geuzaine