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Found 3 papers, 1 papers with code
Simple Multigraph Convolution Networks
Existing multigraph convolution methods either ignore the cross-view interaction among multiple graphs, or induce extremely high computational cost due to standard cross-view polynomial operators.
A Novel Normalized-Cut Solver with Nearest Neighbor Hierarchical Initialization
To address the problems, we propose a novel N-Cut solver designed based on the famous coordinate descent method.
NP$^2$L: Negative Pseudo Partial Labels Extraction for Graph Neural Networks
Moreover, applications of pseudo labels in graph neural networks (GNNs) oversee the difference between graph learning and other machine learning tasks such as message passing mechanism.
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