Join our meetup, learn, connect, share, and get to know your Toronto AI community.
Browse through the latest deep learning, ai, machine learning postings from Indeed for the GTA.
Are you looking to sponsor space, be a speaker, or volunteer, feel free to give us a shout.
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
[link] [comments]