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Representation Learning on Graphs: Methods and Applications

Representation Learning on Graphs: Methods and Applications

www-cs.stanford.edu

To extract structural information from graphs, traditional machine approaches often rely on summary graph statistics (e.g., degrees or clustering coefficients) [6], kernel functions [57], or carefully engineered features to measure local neighborhood structures [39]. However, these approaches are limited because these hand-

  Statistics, Learning, Graph, Graph statistics

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