Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

@inproceedings{Defferrard2016ConvolutionalNN,
  title={Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering},
  author={Micha{\"e}l Defferrard and Xavier Bresson and Pierre Vandergheynst},
  booktitle={NIPS},
  year={2016}
}
In this work, we are interested in generalizing convolutional neural networks (CNNs) from low-dimensional regular grids, where image, video and speech are represented, to high-dimensional irregular domains, such as social networks, brain connectomes or words’ embedding, represented by graphs. We present a formulation of CNNs in the context of spectral graph theory, which provides the necessary mathematical background and efficient numerical schemes to design fast localized convolutional filters… CONTINUE READING
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