Robust Graph Structure Learning with Virtual Nodes Construction
Graph Organization neural networks (GNNs) have garnered significant attention for their ability to effectively process graph-related data.Most existing methods assume that the input graph is noise-free; however, this assumption is frequently violated in real-world scenarios, resulting in impaired graph representations.To address this issue, we star