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[D] Node Embedding and GNN for Graphs with both Continuous and Categorical Atrributes

My problem consists of classifying nodes of graphs (number of vertices <500) , nodes are attributed with both Continuous (some numerical features) and Categorical (CountVectorizer) features. I’ve looked in to various articles both about node embedding and graph neural networks but I’m still not sure what algorithms will be the best fit for my task.

What is your recommended approach for my problem?

Sorry for my short explanation, please ask me if you need more details.

submitted by /u/suddenintent
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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.