Abstract: Fraud detection on dynamic graph (FDDG) is in high demand across many real-world applications, such as financial transaction networks and social networks. A graph neural network (GNN) is an ...
Abstract: In feature learning (FL), structural information shows advantages in retaining information and maintaining stability. Graph diffusion, a graph learning method that can focus on neighborhood ...
In this work we present two main contributions: the first one is a Python implementation of the discrete approximation of the Laplace-Beltrami operator (LBO) (Belkin et al., 2008) allowing us to solve ...
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