I have implemented a heterograph with different node and edge types, and all node types have an individual feature matrix of different sizes. Now I am trying to implement a ‘HeteroGraphConv’ as described here.
My question now is which convolution module to use now for each edge type. Previously, I have been planning on using the RelGraphConv as different edge types are allowed here.
When I define a convolutional layer for each edge type, would it still be necessary to use the RelGraphConv? I am considering hereby the regularisation methods that are applicable. I would also like to ask if the block-diagonal-decomposition would still be useful in this case if no more than one edge type is considered in a convolution.
Would it be sufficient in this case to use the GraphConv module?
Thank you in advance.