Orateur
Aurora Rossi
(COATI, I3S & INRIA d’Université Côte d’Azur)
Description
Recently, Graph Neural Networks have been very successful in solving machine learning tasks such as classification and prediction at the level of nodes, edges and graphs. Their temporal version handles data that evolve over time, such as pandemics and traffic, social networks, financial time series, and brain activity time series. In this poster, I will present how we have implemented some Temporal Graph Neural Networks and their applications.
