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Entropy-centric intelligent computation is a promising approach for dealing with diverse graph computation issues, such as link prediction, graph classification, and graph structure learning. This method has been successfully applied in various settings, including knowledge graphs, social networks, and recommendation systems. However, challenges still exist in modeling complex graph structures and efficiently learning neural graph representations.
