Suppose we apply graph convolutional networks (GCNs) on grid-like graphs (e.g., images) without normalizing adjacency matrix (i.e.,

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Suppose we apply graph convolutional networks (GCNs) on grid-like graphs (e.g., images) without normalizing adjacency matrix (i.e., removing Steps 2-3 in Fig. 10.38). Explain why it is essentially a 2 -D convolution with a special type of filters.

Input: A, adjacency matrix of the input graph of size n x n; X, the node attribute matrix of size n x d; w

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Data Mining Concepts And Techniques

ISBN: 9780128117613

4th Edition

Authors: Jiawei Han, Jian Pei, Hanghang Tong

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