What is the motivation of the graph filter in the Graph Convolutional Networks? For example in the paper
In the Eq.~(3): they perform the convolution the singal $x$ with $g_\theta$ as:
$g_\theta * x = U g_\theta U^Tx$.
What it the role of $g_\theta$ here?Thanks
As I know from signal process convolution means "reverse, shift, multiply and sum". And for graph, what is the intuition for convolution?
I think the graph filter make a role as localization the node with its neighborhoods. To make them share the properties with it. And nice paper recently explain this trick