Learning Convolutional Neural Networks for Graphs

Mathias Niepert, Mohamed Ahmed, Konstantin Kutzkov

Abstract: Numerous important problems can be framed as learning from graph data. We propose a framework for learning convolutional neural networks for arbitrary graphs. These graphs may be undirected, direct...