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• This article uses the ensemble learning to study the imbalanced dataset problem in GNN for the first time. An Boosting-GNN model is proposed to deal with imbalanced datasets in semi-supervised nodes ...

Abstract: As network technologies advance, graph-structured data has grown in importance. Node classification, a key area in analyzing graph data, aims to predict the categories of unlabeled nodes ...

Abstract: Node classification on static graphs has achieved significant success, but achieving accurate node classification on dynamic graphs where node topology, attributes, and labels change over ...

Neuropsychiatric disorder (ND) is often accompanied by abnormal functional connectivity (FC) patterns in specific task contexts. The distinctive task-specific FC patterns can provide valuable features ...