Stability of Graph Neural Networks to Relative Perturbations

international conference on acoustics speech and signal processing, 2019.

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Abstract:

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 heavily on knowledge of the graph for operation. However, in many practical cases the GSO...More

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