Graph Neural Networks (GNNs) exploit signals from node features and the input graph topology to improve node classification task performance. However, these models tend to perform poorly on ...
The second path matrix S(G) collects all the second paths in the graph G. Its characteristic polynomial shows some regularity in several particular graphs, such as paths, cycles, stars and complete ...
If you find this work useful, please cite our paper. Note that the first three authors contributed equally to this work. Graph Neural Networks (GNNs) exploit signals from node features and the input ...
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