Abstract: Graph neural networks (GNNs) have assumed a pivotal role in advancing the domain of graph structure learning, particularly in undirected weighted graphs (UWGs). However, current GNNs ...
Abstract: With the explosive growth of graph data in scale, noise, and structural complexity, existing graph neural networks (GNNs) are reaching a performance bottleneck when simultaneously modelling ...
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