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Found 3 papers, 1 papers with code
Supra-Laplacian Encoding for Transformer on Dynamic Graphs
Fully connected Graph Transformers (GT) have rapidly become prominent in the static graph community as an alternative to Message-Passing models, which suffer from a lack of expressivity, oversquashing, and under-reaching.
Temporal receptive field in dynamic graph learning: A comprehensive analysis
Dynamic link prediction is a critical task in the analysis of evolving networks, with applications ranging from recommender systems to economic exchanges.
ITEM: Improving Training and Evaluation of Message-Passing based GNNs for top-k recommendation
Moreover, we extend the evaluation of GNN models for top-k recommendation tasks with an inductive user-centric protocol, providing a more accurate reflection of real-world applications.
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