AI RESEARCH
What Are Good Positional Encodings for Directed Graphs?
arXiv CS.LG
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ArXi:2407.20912v3 Announce Type: replace Positional encodings (PEs) are essential for building powerful and expressive graph neural networks and graph transformers, as they effectively capture the relative spatial relationships between nodes. Although extensive research has been devoted to PEs in undirected graphs, PEs for directed graphs remain relatively unexplored. This work seeks to address this gap. We first