2 papers
cs.LG2022
Multi-duplicated Characterization of Graph Structures using Information Gain Ratio for Graph Neural Networks
Yuga Oishi, Ken kaneiwa
Various graph neural networks (GNNs) have been proposed to solve node classification tasks in machine learning for graph data. GNNs use the structural information of graph data by…
cs.LG2022
Hierarchical Model Selection for Graph Neural Netoworks
Yuga Oishi, Ken Kaneiwa
Node classification on graph data is a major problem, and various graph neural networks (GNNs) have been proposed. Variants of GNNs such as H2GCN and CPF outperform graph convoluti…