3 citations · 6 across the 4 of their papers we have counts for
4 papers
Template based Graph Neural Network with Optimal Transport Distances
Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli +2
Current Graph Neural Networks (GNN) architectures generally rely on two important components: node features embedding through message passing, and aggregation with a specialized fo…
Semi-relaxed Gromov-Wasserstein divergence with applications on graphs
Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli +2
Comparing structured objects such as graphs is a fundamental operation involved in many learning tasks. To this end, the Gromov-Wasserstein (GW) distance, based on Optimal Transpor…
Online Graph Dictionary Learning
Cédric Vincent-Cuaz, Titouan Vayer, Rémi Flamary +2
Dictionary learning is a key tool for representation learning, that explains the data as linear combination of few basic elements. Yet, this analysis is not amenable in the context…
An Optimal Control Approach to Learning in SIDARTHE Epidemic model
Andrea Zugarini, Enrico Meloni, Alessandro Betti +3
The COVID-19 outbreak has stimulated the interest in the proposal of novel epidemiological models to predict the course of the epidemic so as to help planning effective control str…