Graph convolutional networks (GCNs) have been successfully applied to node representation learning in various real-world applications. However. the performance of GCNs drops rapidly when the labeled data are severely scarce. and the node features are prone to being indistinguishable with stacking more layers. https://www.jmannino.com/special-deal-A-Magazine-Curated-By-Sacai-quick-pick/