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Fig. 1 | Applied Network Science

Fig. 1

From: Joint embedding of structure and features via graph convolutional networks

Fig. 1

Diagram of the overlapping embedding model we propose. Red and blue blocks with a layer name (GC, Dense, Weighted Bilinear) indicate actual layers, with their activation function depicted to the right as a curve in a green circle (either ReLU or sigmoid). Red blocks concern processing for the adjacency matrix, blue blocks processing for the node features. The encoder is made of four parallel GC pipelines producing μA,μX, logσA and logσX (the last two being grayed out in the background). Their output is then combined to create the overlap, then used by the sampler to create the node embeddings. The decoder processes parts of the node embeddings and separately reconstructs the adjacency matrix (top) and the node features (bottom)

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