20 citations
- Électricité de France (France)FR24 papers
- Laboratoire de Mathématiques d'OrsayFR4 papers
- Laboratoire de Probabilités et Modèles AléatoiresFR4 papers
- Laboratoire de Probabilités, Statistique et ModélisationFR4 papers
- Université de LilleFR4 papers
- Institut national de recherche en sciences et technologies du numériqueFR3 papers
- Université Paris-SaclayFR3 papers
- CEA Paris-Saclay - Etablissement de SaclayFR2 papers
- CELESTE: statistique mathématique et apprentissageFR2 papers
- Centre de Recherche en Économie et StatistiqueFR2 papers
- Centre de Recherche en InformatiqueFR2 papers
- Centre de Recherche en Informatique, Signal et Automatique de LilleFR2 papers
10 papers · 1 filter
GraphToolbox: A Configurable Python Framework for Graph Neural Network Forecasting
Eloi Campagne, Yvenn Amara-Ouali, Yannig Goude +1
Electricity forecasting often involves spatially related signals observed over regions, substations, and feeders, and Graph Neural Networks (GNNs) provide a natural way to represen…
DeviceScope: An Interactive App to Detect and Localize Appliance Patterns in Electricity Consumption Time Series
Adrien Petralia, Paul Boniol, Philippe Charpentier +1
In recent years, electricity suppliers have installed millions of smart meters worldwide to improve the management of the smart grid system. These meters collect a large amount of…
Few Labels are all you need: A Weakly Supervised Framework for Appliance Localization in Smart-Meter Series
Adrien Petralia, Paul Boniol, Philippe Charpentier +1
Improving smart grid system management is crucial in the fight against climate change, and enabling consumers to play an active role in this effort is a significant challenge for e…
Online Episodic Convex Reinforcement Learning
Bianca Marin Moreno, Khaled Eldowa, Pierre Gaillard +2
We study online learning in episodic finite-horizon Markov decision processes (MDPs) with convex objective functions, known as the concave utility reinforcement learning (CURL) pro…
Automated Spatio-Temporal Weather Modeling for Load Forecasting
Julie Keisler, Margaux Bregere
Electricity is difficult to store, except at prohibitive cost, and therefore the balance between generation and load must be maintained at all times. Electricity is traditionally m…
MetaCURL: Non-stationary Concave Utility Reinforcement Learning
Bianca Marin Moreno, Margaux Brégère, Pierre Gaillard +1
We explore online learning in episodic loop-free Markov decision processes on non-stationary environments (changing losses and probability transitions). Our focus is on the Concave…