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Learning Convolutional Neural Networks for Graphs

Learning Convolutional Neural Networks for GraphsMathias Labs Europe, Heidelberg, GermanyAbstractNumerous important problems can be framed aslearning from graph data. We propose a frame-work for Learning Convolutional Neural networksfor arbitrary Graphs . These Graphs may be undi-rected, directed, and with both discrete and con-tinuous node and edge attributes. Analogous toimage-based Convolutional Networks that oper-ate on locally connected regions of the input, wepresent a general approach to extracting locallyconnected regions from Graphs .

Learning Convolutional Neural Networks for Graphs 3. Background We provide a brief introduction to the required background in convolutional networks and graph theory. 3.1. Convolutional Neural Networks CNNs were inspired by earlier work that showed that the visual cortex in animals contains complex arrangements

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  Introduction, Network, Graph, Neural, Convolutional, Convolutional networks, Convolutional neural networks

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