An energy-based variational model of ferromagnetic hysteresis for finite element computations. - Vincent François-Lavet; François Henrotte; Laurent Stainier; Ludovic Noels; Christophe Geuzaine (J. Comput. Appl. Math., 2013)

Using approximate dynamic programming for estimating the revenues of a hydrogen-based high-capacity storage device. - Vincent François-Lavet; Raphaël Fonteneau; Damien Ernst (ADPRL, 2014)

Simple Connectome Inference from Partial Correlation Statistics in Calcium Imaging. - Antonio Sutera; Arnaud Joly; Vincent François-Lavet; Zixiao Aaron Qiu; Gilles Louppe; Damien Ernst; Pierre Geurts (Neural Connectomics, 2014)

Imitative Learning for Online Planning in Microgrids. - Samy Aittahar; Vincent François-Lavet; Stefan Lodeweyckx; Damien Ernst; Raphaël Fonteneau (DARE, 2015)

How to Discount Deep Reinforcement Learning: Towards New Dynamic Strategies. - Vincent François-Lavet; Raphaël Fonteneau; Damien Ernst (CoRR, 2015)

Approximate Bayes Optimal Policy Search using Neural Networks. - Michael Castronovo; Vincent François-Lavet; Raphaël Fonteneau; Damien Ernst; Adrien Couëtoux (ICAART (2), 2017)

On overfitting and asymptotic bias in batch reinforcement learning with partial observability. - Vincent François-Lavet; Damien Ernst; Raphael Fonteneau (CoRR, 2017)

Contributions to deep reinforcement learning and its applications in smartgrids. - Vincent François-Lavet (2017)

Reward Estimation for Variance Reduction in Deep Reinforcement Learning. - Joshua Romoff; Alexandre Piché; Peter Henderson 002; Vincent François-Lavet; Joelle Pineau (ICLR (Workshop), 2018)

An Introduction to Deep Reinforcement Learning. - Vincent François-Lavet; Peter Henderson 002; Riashat Islam; Marc G. Bellemare; Joelle Pineau (Found. Trends Mach. Learn., 2018)

Combined Reinforcement Learning via Abstract Representations. - Vincent François-Lavet; Yoshua Bengio; Doina Precup; Joelle Pineau (AAAI, 2019)

Neural Architecture Search for Class-incremental Learning. - Shenyang Huang; Vincent François-Lavet; Guillaume Rabusseau (CoRR, 2019)

On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability. - Vincent François-Lavet; Guillaume Rabusseau; Joelle Pineau; Damien Ernst; Raphael Fonteneau (J. Artif. Intell. Res., 2019)

On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract). - Vincent François-Lavet; Guillaume Rabusseau; Joelle Pineau; Damien Ernst; Raphael Fonteneau (IJCAI, 2020)

Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks. - Maxime Wabartha; Audrey Durand; Vincent François-Lavet; Joelle Pineau (IJCAI, 2020)

Novelty Search in Representational Space for Sample Efficient Exploration. - Ruo Yu Tao; Vincent François-Lavet; Joelle Pineau (NeurIPS, 2020)

RandomNet: Towards Fully Automatic Neural Architecture Design for Multimodal Learning. - Stefano Alletto; Shenyang Huang; Vincent François-Lavet; Yohei Nakata; Guillaume Rabusseau (CoRR, 2020)

Understanding Capacity Saturation in Incremental Learning. - Shenyang Huang; Vincent François-Lavet; Guillaume Rabusseau (Canadian AI, 2021)

Domain Adversarial Reinforcement Learning. - Bonnie Li; Vincent François-Lavet; Thang Doan; Joelle Pineau (CoRR, 2021)

Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey. - Amjad Yousef Majid; Serge Saaybi; Tomas van Rietbergen; Vincent François-Lavet; R. Venkatesha Prasad; Chris J. M. Verhoeven (CoRR, 2021)

Component Transfer Learning for Deep RL Based on Abstract Representations. - Geoffrey van Driessel; Vincent François-Lavet (CoRR, 2021)

Reinforcement Learning with Option Machines. - Floris den Hengst; Vincent François-Lavet; Mark Hoogendoorn; Frank van Harmelen (IJCAI, 2022)

Improving generalization to new environments and removing catastrophic forgetting in Reinforcement Learning by using an eco-system of agents. - Olivier Moulin; Vincent François-Lavet; Paul W. G. Elbers; Mark Hoogendoorn (WI/IAT, 2022)

A Machine With Human-Like Memory Systems. - Taewoon Kim 002; Michael Cochez; Vincent François-Lavet; Mark A. Neerincx; Piek Vossen (CoRR, 2022)

Improving adaptability to new environments and removing catastrophic forgetting in Reinforcement Learning by using an eco-system of agents. - Olivier Moulin; Vincent François-Lavet; Paul W. G. Elbers; Mark Hoogendoorn (CoRR, 2022)

Improving generalization in reinforcement learning through forked agents. - Olivier Moulin; Vincent François-Lavet; Mark Hoogendoorn (CoRR, 2022)

Planning for potential: efficient safe reinforcement learning. - Floris den Hengst; Vincent François-Lavet; Mark Hoogendoorn; Frank van Harmelen (Mach. Learn., 2022)

A Machine with Short-Term, Episodic, and Semantic Memory Systems. - Taewoon Kim 002; Michael Cochez; Vincent François-Lavet; Mark A. Neerincx; Piek Vossen (AAAI, 2023)

A Meta-Reinforcement Learning Algorithm for Causal Discovery. - Andreas W. M. Sauter; Erman Acar; Vincent François-Lavet (CLeaR, 2023)

Improving Generalization in Reinforcement Learning Through Forked Agents. - Olivier Moulin; Vincent François-Lavet; Paul W. G. Elbers; Mark Hoogendoorn (IEA/AIE (2), 2023)

Disentangled (Un)Controllable Features. - Jacob E. Kooi; Mark Hoogendoorn; Vincent François-Lavet (SSCI, 2023)

Latent Assistance Networks: Rediscovering Hyperbolic Tangents in RL. - Jacob E. Kooi; Mark Hoogendoorn; Vincent François-Lavet (CoRR, 2024)

Leveraging Knowledge Graph-Based Human-Like Memory Systems to Solve Partially Observable Markov Decision Processes. - Taewoon Kim 002; Vincent François-Lavet; Michael Cochez (CoRR, 2024)

Comparative performance of intensive care mortality prediction models based on manually curated versus automatically extracted electronic health record data. - 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 (Int. J. Medical Informatics, 2024)

Guideline-informed reinforcement learning for mechanical ventilation in critical care. - Floris den Hengst; Martijn Otten; Paul W. G. Elbers; Frank van Harmelen; Vincent François-Lavet; Mark Hoogendoorn (Artif. Intell. Medicine, 2024)

Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey. - Amjad Yousef Majid; Serge Saaybi; Vincent François-Lavet; R. Venkatesha Prasad; Chris J. M. Verhoeven (IEEE Trans. Neural Networks Learn. Syst., 2024)

Hadamax Encoding: Elevating Performance in Model-Free Atari. - Jacob E. Kooi; Zhao Yang; Vincent François-Lavet (CoRR, 2025)

Learning Abstract World Models with a Group-Structured Latent Space. - Thomas Delliaux; Nguyen-Khanh Vu; Vincent François-Lavet; Elise van der Pol; Emmanuel Rachelson (CoRR, 2025)

Novel RL approach for efficient Elevator Group Control Systems. - Nathan Vaartjes; Vincent François-Lavet (CoRR, 2025)