I am reading about node/graph embeddings. It seems that Neural Networks & the Graph Neural Networks (GNNs) have been applied to a wide range of node-based applications to generate embeddings from graph-data. However, when generating node embeddings learned from GNNs, I don’t seem to understand how edge information are captured. How do you incorporate edge information (if you have a lot of edge features) to generate graph/node embeddings?. Most of the techniques that I came across [1] [2] don’t consider edge information.

Do you have any recommendation of a paper/reference of a method that incorporate edge rich information to generate embeddings?