<ul><li>A straightforward approach to graph embedding involves obtaining node embeddings and aggregating them for all nodes in the graph.</li><li>An enhanced approach involves introducing a virtual node that connects to all other nodes and represents the entire graph.</li><li>Another method involves anonymous random walks to capture graph structural features effectively for embedding purposes.</li><li>Graph embeddings are versatile tools with applications in tasks such as graph classification.</li></ul>

Embedding the Unseen: Techniques for Representing Graphs in Neural Networks

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