Graph Embeddings Insight
Anna, Azalia, and Daniel discuss the importance of edge features in graph embeddings, highlighting the unique approach of focusing on connections between nodes rather than just node features. They delve into how supervised learning with pseudo labels was utilized to train architectures for better understanding and predicting rewards in unseen graphs, essential for policy generalization in graphics.In this clip
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