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[D] Node Embedding & GNN for Graphs

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?

submitted by /u/__Julia
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.