| Simulating tariff impact in electrical energy consumption profiles with conditional variational autoencoders M Brégère, RJ Bessa IEEE Access 8, 131949-131966, 2020 | 19 | 2020 |
| Online hierarchical forecasting for power consumption data M Brégère, M Huard International Journal of Forecasting 38 (1), 339-351, 2022 | 18 | 2022 |
| Target tracking for contextual bandits: Application to demand side management M Brégère, P Gaillard, Y Goude, G Stoltz International Conference on Machine Learning, 754-763, 2019 | 13 | 2019 |
| A variable selection approach in the multivariate linear model: an application to LC-MS metabolomics data M Perrot-Dockès, C Lévy-Leduc, J Chiquet, L Sansonnet, M Brégère, ... Statistical applications in genetics and molecular biology 17 (5), 2018 | 8 | 2018 |
| A multivariate variable selection approach for analyzing LC-MS metabolomics data M Perrot-Dockès, C Lévy-Leduc, J Chiquet, L Sansonnet, M Brégere, ... arXiv preprint arXiv:1704.00076, 2017 | 6 | 2017 |
| A Mirror Descent Approach for Mean Field Control applied to Demande-Side Management BM Moreno, M Brégère, P Gaillard, N Oudjane | 2 | 2023 |
| Efficient model-based concave utility reinforcement learning through greedy mirror descent BM Moreno, M Brégère, P Gaillard, N Oudjane International Conference on Artificial Intelligence and Statistics, 2206-2214, 2024 | 1 | 2024 |
| Efficient Model-Based Concave Utility Reinforcement Learning through Greedy Mirror Descent B Marin Moreno, M Brégère, P Gaillard, N Oudjane arXiv e-prints, arXiv: 2311.18346, 2023 | 1 | 2023 |
| Stochastic Bandit Algorithms for Demand Side Management M Brégère université Paris-Saclay, 2020 | 1 | 2020 |
| MetaCURL: Non-stationary Concave Utility Reinforcement Learning BM Moreno, M Brégère, P Gaillard, N Oudjane arXiv preprint arXiv:2405.19807, 2024 | | 2024 |
| Automated Deep Learning for Load Forecasting J Keisler, S Claudel, G Cabriel, M Brégère arXiv preprint arXiv:2405.08842, 2024 | | 2024 |
| MetaCURL: Non-stationary Concave Utility Reinforcement Learning B Marin Moreno, M Brégère, P Gaillard, N Oudjane arXiv e-prints, arXiv: 2405.19807, 2024 | | 2024 |
| A Bandit Approach with Evolutionary Operators for Model Selection M Brégère, J Keisler arXiv preprint arXiv:2402.05144, 2024 | | 2024 |
| Reimagining Demand-Side Management with Mean Field Learning BM Moreno, M Brégère, P Gaillard, N Oudjane arXiv preprint arXiv:2302.08190, 2023 | | 2023 |
| Reimagining Demand-Side Management with Mean Field Learning B Marin Moreno, M Brégère, P Gaillard, N Oudjane arXiv e-prints, arXiv: 2302.08190, 2023 | | 2023 |
| A variable selection approach in the multivariate linear model: an application to LC-MS metabolomics data M Perrot-Dockès, C Lévy-Leduc, J Chiquet, L Sansonnet, M Brégère, ... Statistical applications in genetics and molecular biology 17 (5), 2018 | | 2018 |
| Management: Application to Thermostatically Controlled Loads BM Moreno, M Brégère, P Gaillard, N Oudjane | | |
