Abstract: In this work, we develop a family of Aligned Entropic Graph Kernels (AEGK) for graph classification. We commence by performing the Continuous-time Quantum Walk (CTQW) on each graph structure ...

Abstract: Graph algorithms are widely used for decision making and knowledge discovery. To ensure their effectiveness, it is essential that their output remains stable even when subjected to small ...

Since Conda needs to perform diffusion on the historical neighbor sequence of a target node, we made some modifications to the model implemented in DyGFormer. Although the original model can also use ...