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Self-supervised learning of graph neural networks (GNNs) aims to learn an accurate representation of the graphs in an unsupervised manner, to obtain transferable representations of them for diverse downstream tasks.
A reduction of a graph to a canonical form and an algebra arising during this reduction
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