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 ...

is called an invariant measure (or invariant distribution) of the Markov process. In the third and final step of Ulam’s approach, the invariant measure is calculated as the eigenvector correspondent ...