3 papers
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.LG2026
Dual-Criterion Curriculum Learning: Application to Temporal Data
Gaspard Abel, Eloi Campagne, Mohamed Benloughmari +1
Curriculum Learning (CL) is a meta-learning paradigm that trains a model by feeding the data instances incrementally according to a schedule, which is based on difficulty progressi…
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…