Graph neural networks have -enabled the application of deep learning to problems that can be described by graphs, which are found throughout the different fields of sci-ence, from physics to biolog…
Popular graph neural networks implement convolution operations on graphs based on polynomial spectral filters. In this paper, we propose a novel graph convolutional layer inspired by the auto-regre…