Abstract: Graph neural networks (GNNs) have emerged as a powerful framework for a wide range of node-level graph learning tasks. However, their performance typically depends on random or minimally ...
Abstract: Semisupervised node classification is a prevalent task on graphs, which involves predicting the labels of unlabeled nodes based on limited labeled data available. At present, centralized ...
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