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Found 2 papers, 1 papers with code
NODE-SELECT: A FLEXIBLE GRAPH NEURAL NETWORK BASED ON REALISTIC PROPAGATION SCHEME
In this paper we propose the NODE-SELECT graph neural network (NSGNN): a novel and flexible graph neural network that uses subsetting filters to learn the contribution from the nodes selected to share their information.
NODE-SELECT: A Graph Neural Network Based On A Selective Propagation Technique
While there exists a wide variety of graph neural networks (GNN) for node classification, only a minority of them adopt mechanisms that effectively target noise propagation during the message-passing procedure.
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