Invariance-Preserving Localized Activation Functions for Graph Neural Networks

29 Mar 2019Luana RuizFernando GamaAntonio G. MarquesAlejandro Ribeiro

Graph signals are signals with an irregular structure that can be described by a graph. Graph neural networks (GNNs) are information processing architectures tailored to these graph signals and made of stacked layers that compose graph convolutional filters with nonlinear activation functions... (read more)

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