Vincent François-Lavet

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 35

Top Topics

Partial Observability

Neural Architecture

Reinforcement Learning

Top Venues

Artif. Intell. Medicine

Publications

Floris den Hengst, Martijn Otten, Paul W. G. Elbers, Frank van Harmelen, Vincent François-Lavet, Mark Hoogendoorn
Guideline-informed reinforcement learning for mechanical ventilation in critical care. Artif. Intell. Medicine 147 (2024)
Jacob E. Kooi, Mark Hoogendoorn, Vincent François-Lavet
Latent Assistance Networks: Rediscovering Hyperbolic Tangents in RL. CoRR (2024)
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
Comparative performance of intensive care mortality prediction models based on manually curated versus automatically extracted electronic health record data. Int. J. Medical Informatics 188 (2024)
Taewoon Kim, Michael Cochez, Vincent François-Lavet, Mark A. Neerincx, Piek Vossen
A Machine with Short-Term, Episodic, and Semantic Memory Systems. AAAI (2023)
Andreas W. M. Sauter, Erman Acar, Vincent François-Lavet
A Meta-Reinforcement Learning Algorithm for Causal Discovery. CLeaR (2023)
Jacob E. Kooi, Mark Hoogendoorn, Vincent François-Lavet
Disentangled (Un)Controllable Features. SSCI (2023)
Olivier Moulin, Vincent François-Lavet, Paul W. G. Elbers, Mark Hoogendoorn
Improving Generalization in Reinforcement Learning Through Forked Agents. IEA/AIE (2) (2023)
Floris den Hengst, Vincent François-Lavet, Mark Hoogendoorn, Frank van Harmelen
Reinforcement Learning with Option Machines. IJCAI (2022)
Taewoon Kim, Michael Cochez, Vincent François-Lavet, Mark A. Neerincx, Piek Vossen
A Machine with Short-Term, Episodic, and Semantic Memory Systems. CoRR (2022)
Olivier Moulin, Vincent François-Lavet, Mark Hoogendoorn
Improving generalization in reinforcement learning through forked agents. CoRR (2022)
Taewoon Kim, Michael Cochez, Vincent François-Lavet, Mark A. Neerincx, Piek Vossen
A Machine With Human-Like Memory Systems. CoRR (2022)
Jacob E. Kooi, Mark Hoogendoorn, Vincent François-Lavet
Disentangled (Un)Controllable Features. CoRR (2022)
Andreas Sauter, Erman Acar, Vincent François-Lavet
A Meta-Reinforcement Learning Algorithm for Causal Discovery. CoRR (2022)
Floris den Hengst, Vincent François-Lavet, Mark Hoogendoorn, Frank van Harmelen
Planning for potential: efficient safe reinforcement learning. Mach. Learn. 111 (6) (2022)
Olivier Moulin, Vincent François-Lavet, Paul W. G. Elbers, Mark Hoogendoorn
Improving adaptability to new environments and removing catastrophic forgetting in Reinforcement Learning by using an eco-system of agents. CoRR (2022)
Geoffrey van Driessel, Vincent François-Lavet
Component Transfer Learning for Deep RL Based on Abstract Representations. CoRR (2021)
Amjad Yousef Majid, Serge Saaybi, Tomas van Rietbergen, Vincent François-Lavet, R. Venkatesha Prasad, Chris J. M. Verhoeven
Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey. CoRR (2021)
Bonnie Li, Vincent François-Lavet, Thang Doan, Joelle Pineau
Domain Adversarial Reinforcement Learning. CoRR (2021)
Shenyang Huang, Vincent François-Lavet, Guillaume Rabusseau
Understanding Capacity Saturation in Incremental Learning. Canadian Conference on AI (2021)
Ruo Yu Tao, Vincent François-Lavet, Joelle Pineau
Novelty Search in Representational Space for Sample Efficient Exploration. NeurIPS (2020)
Maxime Wabartha, Audrey Durand, Vincent François-Lavet, Joelle Pineau
Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks. IJCAI (2020)
Vincent François-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst, Raphael Fonteneau
On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract). IJCAI (2020)
Stefano Alletto, Shenyang Huang, Vincent François-Lavet, Yohei Nakata, Guillaume Rabusseau
RandomNet: Towards Fully Automatic Neural Architecture Design for Multimodal Learning. CoRR (2020)
Ruo Yu Tao, Vincent François-Lavet, Joelle Pineau
Novelty Search in representational space for sample efficient exploration. CoRR (2020)
Vincent François-Lavet, Yoshua Bengio, Doina Precup, Joelle Pineau
Combined Reinforcement Learning via Abstract Representations. AAAI (2019)
Vincent François-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst, Raphael Fonteneau
On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability. J. Artif. Intell. Res. 65 (2019)
Shenyang Huang, Vincent François-Lavet, Guillaume Rabusseau
Neural Architecture Search for Class-incremental Learning. CoRR (2019)
Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. CoRR (2018)
Joshua Romoff, Peter Henderson, Alexandre Piché, Vincent François-Lavet, Joelle Pineau
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. CoRL (2018)
Vincent François-Lavet, Yoshua Bengio, Doina Precup, Joelle Pineau
Combined Reinforcement Learning via Abstract Representations. CoRR (2018)
Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. ICLR (Workshop) (2018)
Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau
An Introduction to Deep Reinforcement Learning. Found. Trends Mach. Learn. 11 (3-4) (2018)
Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau
An Introduction to Deep Reinforcement Learning. CoRR (2018)
Vincent François-Lavet, Damien Ernst, Raphael Fonteneau
On overfitting and asymptotic bias in batch reinforcement learning with partial observability. CoRR (2017)
Michael Castronovo, Vincent François-Lavet, Raphaël Fonteneau, Damien Ernst, Adrien Couëtoux
Approximate Bayes Optimal Policy Search using Neural Networks. ICAART (2) (2017)
Samy Aittahar, Vincent François-Lavet, Stefan Lodeweyckx, Damien Ernst, Raphaël Fonteneau
Imitative Learning for Online Planning in Microgrids. DARE (2015)
Vincent François-Lavet, Raphaël Fonteneau, Damien Ernst
How to Discount Deep Reinforcement Learning: Towards New Dynamic Strategies. CoRR (2015)
Vincent François-Lavet, Raphaël Fonteneau, Damien Ernst
Using approximate dynamic programming for estimating the revenues of a hydrogen-based high-capacity storage device. ADPRL (2014)
Antonio Sutera, Arnaud Joly, Vincent François-Lavet, Zixiao Aaron Qiu, Gilles Louppe, Damien Ernst, Pierre Geurts
Simple connectome inference from partial correlation statistics in calcium imaging. CoRR (2014)
Antonio Sutera, Arnaud Joly, Vincent François-Lavet, Zixiao Aaron Qiu, Gilles Louppe, Damien Ernst, Pierre Geurts
Simple Connectome Inference from Partial Correlation Statistics in Calcium Imaging. Neural Connectomics (2014)
Vincent François-Lavet, François Henrotte, Laurent Stainier, Ludovic Noels, Christophe Geuzaine
An energy-based variational model of ferromagnetic hysteresis for finite element computations. J. Comput. Appl. Math. 246 (2013)