Abstract: Graph Neural Networks (GNNs) have become a powerful tool in order to learn from graph-structured data. Their ability to capture complex relationships and dependencies within graph structures ...

You can connect virtual networks to each other with virtual network peering. These virtual networks can be in the same region or different regions (also known as global virtual network peering). Once ...

Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...