75 citations · 80 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 75 cited
NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification
Qitian Wu, Wentao Zhao, Zenan Li +2
Graph neural networks have been extensively studied for learning with inter-connected data. Despite this, recent evidence has revealed GNNs' deficiencies related to over-squashing,…
cs.LG2020★ 5 cited
A pipeline for fair comparison of graph neural networks in node classification tasks
Wentao Zhao, Dalin Zhou, Xinguo Qiu +1
Graph neural networks (GNNs) have been investigated for potential applicability in multiple fields that employ graph data. However, there are no standard training settings to ensur…