Abstract A graph neural network with three bipartite graphs based on a topology of a network, Gp,l connecting paths in a network to their links, Gl,n connecting links to nodes defining the links, and Gp,n connecting paths to nodes, wherein each vertex of the bipartite graphs has a hidden state to be passed to its neighbours during iterated message passing convolutions, the graph neural network is injected network parameters and load are injected into the above graphs. A network characteristic combines the resulting outputs using a fully connected layer. |
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