Deep learning for dynamic graphs: models and benchmarks

1 code implementation • 12 Jul 2023 • Alessio Gravina, Davide Bacciu

Recent progress in research on Deep Graph Networks (DGNs) has led to a maturation of the domain of learning on graphs.

Model Selection Representation Learning

Anti-Symmetric DGN: a stable architecture for Deep Graph Networks

1 code implementation • 18 Oct 2022 • Alessio Gravina, Davide Bacciu, Claudio Gallicchio

Deep Graph Networks (DGNs) currently dominate the research landscape of learning from graphs, due to their efficiency and ability to implement an adaptive message-passing scheme between the nodes.