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Stability Of Graph Neural Networks To Relative Perturbations

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IEEE ICASSP 2020 Virtual Conference May 2020

Graph neural networks (GNNs), consisting of a cascade of layers applying a graph convolution followed by a pointwise nonlinearity, have become a powerful architecture to process signals supported on graphs. Graph convolutions (and thus, GNNs), rely heavil

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Stability Of Graph Neural Networks To Relative Perturbations

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Graph neural networks (GNNs), consisting of a cascade of layers applying a graph convolution followed by a pointwise nonlinearity, have become a powerful architecture to process signals supported on graphs. Graph convolutions (and thus, GNNs), rely heavil