Pre-Training Graph Neural Networks for Generic Structural Feature Extraction
arXiv: Learning, 2019.
Graph neural networks (GNNs) are shown to be successful in modeling applications with graph structures. However, training an accurate GNN model requires a large collection of labeled data and expressive features, which might be inaccessible for some applications. To tackle this problem, we propose a pre-training framework that captures ...More
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