Back
  1. Home
  2. Profile of Vincent François-Lavet (ULiège)
Profil

François-Lavet Vincent

Main Referenced Co-authors
Ernst, Damien  (10)
Fonteneau, Raphaël  (7)
Geuzaine, Christophe  (2)
Henrotte, François (2)
Léonard, Grégoire  (2)
Main Referenced Keywords
hydrogen (2); Reinforcement learning (2); storage (2); artificial neural networks (1); Bayesian reinforcement learning (1);
Main Referenced Unit & Research Centers
Computational & Multiscale Mechanics of Materials (1)
Systems and Modeling Research Unit (1)
Main Referenced Disciplines
Computer science (6)
Electrical & electronics engineering (3)
Energy (2)
Materials science & engineering (2)
Chemical engineering (1)

Publications (total 13)

The most downloaded
3674 downloads
François-Lavet, V., Taralla, D., Ernst, D., & Fonteneau, R. (2016). Deep Reinforcement Learning Solutions for Energy Microgrids Management. In European Workshop on Reinforcement Learning (EWRL 2016). https://hdl.handle.net/2268/203831

The most cited

35 citations (Scopus®)

François-Lavet, V., Henrotte, F., Stainier, L., Noels, L., & Geuzaine, C. (July 2013). An Energy-Based Variational Model of Ferromagnetic Hysteresis for Finite Element Computations. Journal of Computational and Applied Mathematics, 246, 243–250. doi:10.1016/j.cam.2012.06.007 https://hdl.handle.net/2268/124340

François-Lavet, V. (2017). Contributions to deep reinforcement learning and its applications in smartgrids [Doctoral thesis, ULiège - Université de Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/214216

Castronovo, M., François-Lavet, V., Fonteneau, R., Ernst, D., & Couëtoux, A. (2017). Approximate Bayes Optimal Policy Search using Neural Networks. In Proceedings of the 9th International Conference on Agents and Artificial Intelligence (ICAART 2017). doi:10.5220/0006191701420153
Peer reviewed

François-Lavet, V., Taralla, D., Ernst, D., & Fonteneau, R. (2016). Deep Reinforcement Learning Solutions for Energy Microgrids Management. In European Workshop on Reinforcement Learning (EWRL 2016).
Peer reviewed

François-Lavet, V., Gemine, Q., Ernst, D., & Fonteneau, R. (2016). Towards the Minimization of the Levelized Energy Costs of Microgrids using both Long-term and Short-term Storage Devices. In Smart Grid: Networking, Data Management, and Business Models (pp. 295-319). CRC Press.
Peer reviewed

Aittahar, S., François-Lavet, V., Lodeweyckx, S., Ernst, D., & Fonteneau, R. (2015). Imitative Learning for Online Planning in Microgrids. In W. L. Woon, A. Zeyar, ... M. Stuart (Eds.), Data Analytics for Renewable Energy Integration (pp. 1-15). Springer. doi:10.1007/978-3-319-27430-0_1
Peer reviewed

François-Lavet, V., Fonteneau, R., & Ernst, D. (2015). How to Discount Deep Reinforcement Learning: Towards New Dynamic Strategies. In NIPS 2015 Workshop on Deep Reinforcement Learning.
Peer reviewed

Léonard, G., François-Lavet, V., Ernst, D., Meinrenken, C. J., & Lackner, K. S. (2015). Electricity storage with liquid fuels in a zone powered by 100% variable renewables [Paper presentation]. 12th International Conference on the European Energy Market - EEM 2015, Lisbon, Portugal.

Léonard, G., François-Lavet, V., Ernst, D., Meinrenken J., C., & Lackner S., K. (2015). Electricity storage with liquid fuels in a zone powered by 100% variable renewables. In Proceedings of the 12th International Conference on the European Energy Market - EEM15. doi:10.1109/EEM.2015.7216634
Peer reviewed

François-Lavet, V., Fonteneau, R., & Ernst, D. (2014). Using approximate dynamic programming for estimating the revenues of a hydrogen-based high-capacity storage device. IEEE Symposium Series on Computational Intelligence. doi:10.1109/ADPRL.2014.7010624
Peer reviewed

Sutera, A., Joly, A., François-Lavet, V., Qiu, Z., Louppe, G., Ernst, D., & Geurts, P. (2014). Simple connectome inference from partial correlation statistics in calcium imaging. In J. Soriano, D. Battaglia, I. Guyon, V. Lemaire, J. Orlandi, ... B. Ray (Eds.), Neural Connectomics Challenge. Springer.
Peer reviewed

François-Lavet, V., Fonteneau, R., & Ernst, D. (2014). Estimating the revenues of a hydrogen-based high-capacity storage device: methodology and results. In Proceedings des 9èmes Journée Francophones de Planification, Décision et Apprentissage.
Peer reviewed

François-Lavet, V., Henrotte, F., Stainier, L., Noels, L., & Geuzaine, C. (July 2013). An Energy-Based Variational Model of Ferromagnetic Hysteresis for Finite Element Computations. Journal of Computational and Applied Mathematics, 246, 243–250. doi:10.1016/j.cam.2012.06.007
Peer Reviewed verified by ORBi

François-Lavet, V., Henrotte, F., Stainier, L., Noels, L., & Geuzaine, C. (2011). Vectorial Incremental Nonconservative Consistent Hysteresis model. In M. Hogge, R. Van Keer, B. Malengier, M. Slodicka, E. Béchet, C. Geuzaine, L. Noels, J.-F. Remacle, ... E. Dick (Eds.), Proceedings of the 5th International Conference on Advanded COmputational Methods in Engineering (ACOMEN2011) (pp. 10).
Peer reviewed

Contact ORBi