Topology-induced Operators Reveal Complementary Graph Representations without Training
This work shows that informative embeddings can be derived without complicated model design and gradient-based training, and suggests that informative graph embeddings can arise from carefully chosen topological transformations before any learning operation is applied.
Meng Qin, Jin-Qiang Cui, Hong-Wei Zheng et al.
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