Pardis Sadatian Moghaddam

AquaGraph and AGN-Net: A Biologically Inspired Framework for Scalable and Adaptive Graph Neural Networks

Graph Neural Networks (GNNs) are powerful tools for learning on relational data, but many real-world graphs evolve continuously, and existing Dynamic GNNs (DGNNs) often process large portions of the graph at every time step. In many temporal graphs, change is local: only a small, shifting subset of nodes is active at a...