Graph Neural Networks (GNNs) have been proposed to learn graph representations for various graph mining tasks such as link prediction and node classification. These methods aggregate information from ...

Existing GNNs usually conduct the layer-wise message propagation via the ‘full’ aggregation of all neighborhood information which are usually sensitive to the structural noises existed in the graphs, ...