Target Tracking for Contextual Bandits: Application to Demand Side Management. - Margaux Brégère; Pierre Gaillard; Yannig Goude; Gilles Stoltz (ICML, 2019)

Simulating Tariff Impact in Electrical Energy Consumption Profiles With Conditional Variational Autoencoders. - Margaux Brégère; Ricardo J. Bessa (IEEE Access, 2020)

Online Hierarchical Forecasting for Power Consumption Data. - Margaux Brégère; Malo Huard (CoRR, 2020)

Reimagining Demand-Side Management with Mean Field Learning. - Bianca Marin Moreno; Margaux Brégère; Pierre Gaillard; Nadia Oudjane (CoRR, 2023)

Efficient Model-Based Concave Utility Reinforcement Learning through Greedy Mirror Descent. - Bianca Marin Moreno; Margaux Brégère; Pierre Gaillard; Nadia Oudjane (AISTATS, 2024)

Automated Deep Learning for load forecasting. - Julie Keisler; Sandra Claudel; Gilles Cabriel; Margaux Brégère (AutoML, 2024)

MetaCURL: Non-stationary Concave Utility Reinforcement Learning. - Bianca Marin Moreno; Margaux Brégère; Pierre Gaillard; Nadia Oudjane (NeurIPS, 2024)

A Bandit Approach with Evolutionary Operators for Model Selection. - Margaux Brégère; Julie Keisler (CoRR, 2024)

Automated Spatio-Temporal Weather Modeling for Load Forecasting. - Julie Keisler; Margaux Brégère (CoRR, 2024)

AutoML Algorithms for Online Generalized Additive Model Selection: Application to Electricity Demand Forecasting. - Keshav Das; Julie Keisler; Margaux Brégère; Amaury Durand (CoRR, 2025)

Online Episodic Convex Reinforcement Learning. - Bianca Marin Moreno; Khaled Eldowa; Pierre Gaillard; Margaux Brégère; Nadia Oudjane (CoRR, 2025)

(Online) Convex Optimization for Demand-Side Management: Application to Thermostatically Controlled Loads. - Bianca Marin Moreno; Margaux Brégère; Pierre Gaillard; Nadia Oudjane (J. Optim. Theory Appl., 2025)