Graph Structure Understanding
New algorithms to learn node and graph similarity on scale.
DDGK: Learning Graph Representations for Deep Divergence Graph Kernels
Can neural networks learn to compare graphs without feature engineering? In this paper, we show that it is possible to learn representations for graph similarity with neither domain knowledge nor supervision (i.e. feature engineering or labeled …