Publications

List and links to papers, software and talks.

Articles

• AutoML Algorithms for Online Generalized Additive Model Selection: Application to Electricity Demand Forecasting, Keshav Das, Julie Keisler, Margaux Brégère, and Amaury Durand, Submitted, 2025

• (Online) Convex Optimization for Demand-Side Management: Application to Thermostatically Controlled Loads, Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard and Nadia Oudjane, Journal of Optimization Theory and Applications, 2025

• Spatio-temporal Clustering and Reconciliation for Regional Electricity Demand Forecasting, Margaux Brégère and Raffaele Mattera, Submitted, 2024

• Automated Spatio-Temporal Weather Modeling for Load Forecasting, Julie Keisler and Margaux Brégère, International Ruhr Energy Conference, 2024, Best paper award

• MetaCURL: Non-stationary Concave Utility Reinforcement Learning, Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard and Nadia Oudjane, NeurIPS, 2024

• A bandit approach with evolutionary operators for model selection: Application to neural architecture optimization for image classification, Margaux Brégère and Julie Keisler, Submitted, 2024

• Automated Deep Learning for load forecasting, Julie Keisler, Sandra Claudel, Gilles Cabriel, Margaux Brégère, AUTOML (International Conference on Automated Machine Learning), 2024

• Efficient Model-Based Concave Utility Reinforcement Learning through Greedy Mirror Descent, Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard and Nadia Oudjane, AISTATS (The 21st International Conference on Artificial Intelligence and Statistics), 2024

• Online Hierarchical Forecasting for Power Consumption Data, Margaux Brégère and Malo Huard, International Journal of Forecasting, 2022, IIF-Tao Hong Award

• Simulating tariff impact in electrical energy consumption profiles with conditional variational autoencoders, Margaux Brégère and Ricardo Bessa, IEEE Access, 2020

• Target Tracking for Contextual Bandits : Application to Demand Side Management, Margaux Brégère, Pierre Gaillard, Yannig Goude and Gilles Stoltz, ICML (International Conference on Machine Learning), pages 754–763, 2019

• A variable selection approach in the multivariate linear model : An application to LC-MS metabolomics data, Marie Perrot-Dockès, Céline Lévy-Leduc, Julien Chiquet, Laure Sansonnet, Margaux Brégère, Marie-Pierre Etienne, Stéphane Robin and Grégory Genta-Jouve, Statistical Applications in Genetics and Molecular Biology, vol. 17, n. 5, 2018

Software of students

• DRAGON (DiRected Acyclic Graphs OptimizatioN), python package for AutoML developed by Julie Keisler during her PhD (2025)
• XPC (eXplainability through Positive Contributions), python package for explainability (Shapley values based approach) developed by Gaspard Berthelier during his end-of-studies internship (2024)

PhD

• Stochastic Bandit Algorithms for Demand Side Management, University of Paris Saclay (Laboratoire de Mathématiques d’Orsay, EDF R&D, Inria Paris), under the supervision of Gilles Stoltz, Yannig Goude and Pierre Gaillard, 2020, ThinkSmartGrids 2022 awards - AMIES 2021 award

Talks

• Rencontres MathTech 2025 (FMJH), IHES, Bures-sur-Yvette, France, January 2025
• Forecasting & optimization:streamlining supply chains, ESSEC Research Center, La Défense, France, December 2024
• Meetup Paris Women in Machine Learning & Data Science, Critéo AI Lab, Paris, France, April 2024
• Séminaire Parisien de Statistique, Institut Henri-Poincaré, Paris, France, April 2024
• WPI-Workshop on Stochastics, Statistics, Machine Learning and their Applications of Sustainable Finance and Energy Markets, Wolfgang-Pauli Institute Vienna, Austria, September 2023
• IIF Workshop on Forecast Reconciliation, Monash University, Prato, Italy, September 2023
• Women in Data Science Conference, online, April 2023
• New Year’s address of the ThinkSmartGrids association, online, January 2022
• Phiméca workshop, Henri Poincaré Institut, Paris November 2021
• FrENBIS conference, online, September 2021
• PhD defense, online, December 2020
• Lab Meeting of Center for Power and Energy Systems, online, November 2020
• IA Summer School of BNP, Campus BNP Paribas, Louveciennes, August 2019
• International Conference on Machine Learning, Long Beach, USA, June 2019
• Statistics Days, Nancy, June 2019
• 8th Young Statisticians Meeting, Porquerolles, April 2019
• Machine Learning in Real Word, Critéo Lab, Paris, October 2019
• Workshop on energy transition WTE 2018, EDF Lab, Palaiseau, November 2018
• Junior Conference on Data Science and Engineering, Orsay, September 2017

Others

• Master Class Lycéennes - Le problème du bandit à K bras, Fondation Séphora Berrebi, Institut Henri-Poincaré, Paris, France, April 2025
• Round table on mathematics in companies for the 24ème Forum des jeunes mathématiciennes et mathématiciens, November 2024
• Interview for docteurs SPI, August 2022
• Feedback on CIFRE PhD, City of Sciences, Paris, October 2019, 2020 and 2024