Abstract: In recent years, Graph Neural Networks (GNNs) have achieved significant success in graph-based tasks. However, they still face challenges in complex scenarios, particularly in integrating ...

A PyTorch implementation of the DeFoG model for training and sampling discrete graph flows. (Please update to the latest commit. Recent fixes have been applied.) Working with directed graphs? Consider ...

Abstract: Dynamic graphs arise in various real-world applications, and it is often welcomed to model the dynamics in continuous time domain for its flexibility. This paper aims to design an ...