Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning
Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning
Many interesting problems in machine learning are being revisited with new deep learning tools. For graph-based semi-supervised learning, a recent important development is graph convolutional networks (GCNs), which nicely integrate local vertex features and graph topology in the convolutional layers. Although the GCN model compares favorably with other state-of-the-art methods, …