Abstract: Temporal graphs are commonly used to represent complex systems and track the evolution of their constituents over time. Visualizing these graphs is crucial as it allows one to quickly ...

Abstract: Amid the era of rapid integration of Graph Neural Networks (GNNs) into diverse applications, such as anomaly detection in heterogeneous graphs, the pursuit of interpretable and dependable ...