Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...

Graphs are a ubiquitous data structure and a universal language for representing objects and complex interactions. They can model a wide range of real-world systems, such as social networks, chemical ...

Linux has long been the backbone of modern computing, serving as the foundation for servers, cloud infrastructures, embedded systems, and supercomputers. As artificial intelligence (AI) and machine ...