Yes, though connections may carry data themselves, in which case an adjacency matrix isn't enough. Some problem domains can be modeled in graphs where nodes are simply connected, but others may require a connection type to be defined (eg: "friend of" / "worked with" / "parent of") and even more data besides just a type (eg: if representing physical objects as a graph, you could encode distances as edge attributes).
So there's multiple ways to represent the graph structure, adj matrix being just one of them but that will have to be part of the input to the network.
miguelventura t1_iusrlt1 wrote
Reply to [D] Graph neural networks by No_Captain_856
Yes, though connections may carry data themselves, in which case an adjacency matrix isn't enough. Some problem domains can be modeled in graphs where nodes are simply connected, but others may require a connection type to be defined (eg: "friend of" / "worked with" / "parent of") and even more data besides just a type (eg: if representing physical objects as a graph, you could encode distances as edge attributes).
So there's multiple ways to represent the graph structure, adj matrix being just one of them but that will have to be part of the input to the network.