Vincent François-Lavet

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Joelle PineauSchool of Computer Science, McGill University; FAIR, Meta AI; MilaVerified email at cs.mcgill.ca
Peter HendersonPrinceton UniversityVerified email at princeton.edu
Damien ErnstProfessor of Electrical Engineering and Computer Science, ULiègeVerified email at uliege.be
Raphael FonteneauResearcher @ University of Liège, Liège, BelgiumVerified email at ulg.ac.be
Marc G. BellemareReliant AIVerified email at reliant.ai
Riashat IslamResearch ScientistVerified email at mail.mcgill.ca
Mark HoogendoornFull Professor of Artificial Intelligence, Vrije Universiteit AmsterdamVerified email at cs.vu.nl
Guillaume RabusseauAssistant Professor - Canada CIFAR AI Chair, Université de Montréal / MilaVerified email at iro.umontreal.ca
David TarallaPhD Student in Computer Science & Engineering, University of LiègeVerified email at ulg.ac.be
Doina PrecupDeepMind and McGill UniversityVerified email at cs.mcgill.ca
Floris den HengstVrije Universiteit AmsterdamVerified email at vu.nl
Christophe GeuzaineFull Professor, University of LiègeVerified email at uliege.be
François HenrotteACE - University of LiègeVerified email at uliege.be
Shenyang HuangMcGill University, Montreal Institute for Learning Algorithms (Mila)Verified email at mail.mcgill.ca
Frank van HarmelenDept. of Computer Science, Vrije Universiteit AmsterdamVerified email at vu.nl
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Joshua RomoffUbisoft La ForgeVerified email at ubisoft.com
Alexandre PichéServiceNow Research, MilaVerified email at mail.mcgill.ca
Ruo Yu TaoBrown UniversityVerified email at brown.edu
Taewoon KimHumemAIVerified email at humem.ai

Vincent François-Lavet

VU Amsterdam

Verified email at vu.nl

reinforcement learning deep learning representation learning machine learning artificial intelligence


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An introduction to deep reinforcement learning V François-Lavet, P Henderson, R Islam, MG Bellemare, J Pineau Foundations and Trends® in Machine Learning, 2018	1995	2018
Deep reinforcement learning solutions for energy microgrids management V François-Lavet, D Taralla, D Ernst, R Fonteneau EWRL 2016, 2016	210	2016
How to discount deep reinforcement learning: Towards new dynamic strategies V François-Lavet, R Fonteneau, D Ernst Deep Reinforcement Learning Workshop, NIPS 2015, 2015	164	2015
Combined Reinforcement Learning via Abstract Representations V François-Lavet, Y Bengio, D Precup, J Pineau Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), 2019	113	2019
Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey A Majid, S Saaybi, T van Rietbergen, V Francois-Lavet, RV Prasad, ... IEEE Transactions on Neural Networks and Learning Systems, 2023	74	2023
Reward Estimation for Variance Reduction in Deep Reinforcement Learning J Romoff, A Piché, P Henderson, V Francois-Lavet, J Pineau Conference on Robot Learning (CoRL 2018), 2018	55	2018
An energy-based variational model of ferromagnetic hysteresis for finite element computations V François-Lavet, F Henrotte, L Stainier, L Noels, C Geuzaine Journal of Computational and Applied Mathematics 246, 243-250, 2013	53	2013
Novelty Search in representational space for sample efficient exploration RY Tao, V François-Lavet, J Pineau Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), 2020	52	2020
Domain Adversarial Reinforcement Learning B Li, V François-Lavet, T Doan, J Pineau Deep RL workshop, NeurIPS 2020, 2021	45	2021
On overfitting and asymptotic bias in batch reinforcement learning with partial observability V François-Lavet, G Rabusseau, J Pineau, D Ernst, R Fonteneau Journal of Artificial Intelligence Research 65, 1-30, 2019	40	2019
Study of passive and active attitude control systems for the OUFTI nanosatellites V Francois-Lavet University of Liège, Faculty of Applied Sciences, Belgium, 2010	38	2010
Optimizing Home Energy Management and Electric Vehicle Charging with Reinforcement Learning D Wu, G Rabusseau, V François-lavet, D Precup, B Boulet ALA 2018, 2018	33	2018
Contributions to deep reinforcement learning and its applications in smartgrids V François-Lavet PQDT-Global, 2017	30	2017
Reinforcement learning for radiotherapy dose fractioning automation G Moreau, V François-Lavet, P Desbordes, B Macq Biomedicines 9 (2), 214, 2021	24	2021
Vectorial incremental nonconservative consistent hysteresis model V François-Lavet, F Henrotte, L Stainier, L Noels, C Geuzaine 5th International Conference on Advanded COmputational Methods in …, 2011	24	2011
Planning for potential: efficient safe reinforcement learning F Den Hengst, V François-Lavet, M Hoogendoorn, F van Harmelen Machine Learning 111 (6), 2255-2274, 2022	22	2022
Towards the minimization of the levelized energy costs of microgrids using both long-term and short-term storage devices V François-Lavet, Q Gemine, D Ernst, R Fonteneau 9781498719704, 2016	22	2016
Simple connectome inference from partial correlation statistics in calcium imaging A Sutera, A Joly, V François-Lavet, A Qiu, G Louppe, D Ernst, P Geurts Neural Connectomics Workshop, 23-35, 2015	22	2015
A meta-reinforcement learning algorithm for causal discovery A Sauter, E Acar, V François-Lavet CLeaR (Causal Learning and Reasoning) 2023, 2023	19	2023
An introduction to deep reinforcement learning. arXiv 2018 V Francois-Lavet, P Henderson, R Islam, MG Bellemare, J Pineau arXiv preprint arXiv:1811.12560, 0	18

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