Deep Inductive Graph Representation Learning.

This paper presents a general inductive graph representation learning framework called $\text{DeepGL}$DeepGL for learning deep node and edge features that generalize across-networks. In particular, $\text{DeepGL}$DeepGL begins by deriving a set of base features from the graph (e.g., graphlet features) and automatically learns a multi-layered hierarchical graph representation where each successive ...