Vincent François-Lavet

Publication Activity (10 Years)

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

Top Topics

Reinforcement Learning

Neural Architecture

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)
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)