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}
}
Convolutional neural networks (CNNs) have greatly improved state-of-the-art performances in a number of fields, notably computer vision and natural language processing. In this work, we are interested in generalizing the formulation of CNNs from low-dimensional regular Euclidean domains, where images (2D), videos (3D) and audios (1D) are represented, to high-dimensional irregular domains such as social networks or biological networks represented by graphs. This paper introduces a formulation of… CONTINUE READING

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