This motivate us to construct a spectral-based GCNN for directed graphs. In this paper, we propose a scalable graph convolutional neural network with fast localized convolution operators derived from ...

In this paper, we introduce sampling strategies into SGN, and design a novel sampling subgraph network model, which is scale-controllable and of higher diversity. We also present a structural feature ...