1 code implementation • 17 Feb 2021 • Steph-Yves Louis, Alireza Nasiri, Fatima J. Rolland, Cameron Mitro, Jianjun Hu
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.
no code implementations • 1 Jan 2021 • Steph-Yves Louis, Alireza Nasiri, Fatima Christina Rolland, Cameron Mitro, Jianjun Hu
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.