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In this paper, we derive generalization bounds for the two primary classes of graph neural networks (GNNs), namely graph convolutional networks (GCNs) and message passing GNNs (MPGNNs), via a PAC-Bayesian approach.
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Wengong Jin, Kevin Yang, Regina Barzilay, and Tommi Jaakkola · 2018
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