activity
20212026
most citedLeveraging Graph Neural Networks to Forecast Electricity Consumption

2 citations · 3 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2026

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…

stat.AP2026

Spatio-temporal modelling of electric vehicle charging demand

Kaoutar Bouaachra, Yvenn Amara-Ouali, Yannig Goude +1

Accurate forecasting of electric vehicle (EV) charging demand is critical for grid management and infrastructure planning. Yet the field continues to rely on legacy benchmarks; suc…

cs.LG2026

Cascaded Transfer: Learning Many Tasks under Budget Constraints

Eloi Campagne, Yvenn Amara-Ouali, Yannig Goude +2

In distributed applications, such as energy demand forecasting at the substation level or federated learning, a large number of related tasks must be learned by different models, w…

cs.LG2025

Graph Neural Networks for Electricity Load Forecasting

Eloi Campagne, Yvenn Amara-Ouali, Yannig Goude +2

Forecasting electricity demand is increasingly challenging as energy systems become more decentralized and intertwined with renewable sources. Graph Neural Networks (GNNs) have rec…

stat.ML2024★ 1 cited

Conformal Prediction for Hierarchical Data

Guillaume Principato, Gilles Stoltz, Yvenn Amara-Ouali +3

We consider conformal prediction for multivariate data and focus on hierarchical data, where some components are linear combinations of others. Intuitively, the hierarchical struct…

cs.LG2024★ 2 cited

Leveraging Graph Neural Networks to Forecast Electricity Consumption

Eloi Campagne, Yvenn Amara-Ouali, Yannig Goude +1

Accurate electricity demand forecasting is essential for several reasons, especially as the integration of renewable energy sources and the transition to a decentralized network pa…

cs.DB2023

Forecasting Electric Vehicle Charging Station Occupancy: Smarter Mobility Data Challenge

Yvenn Amara-Ouali, Yannig Goude, Nathan Doumèche +10

The transport sector is a major contributor to greenhouse gas emissions in Europe. Shifting to electric vehicles (EVs) powered by a low-carbon energy mix would reduce carbon emissi…

cs.LG2021

Daily peak electrical load forecasting with a multi-resolution approach

Yvenn Amara-Ouali, Matteo Fasiolo, Yannig Goude +1

In the context of smart grids and load balancing, daily peak load forecasting has become a critical activity for stakeholders of the energy industry. An understanding of peak magni…