Most existing graph neural networks (GNNs) are proposed without considering the selection bias in data, i.e., the inconsistent distribution between the training set with the test set. In reality, the ...

Subgraph pattern matching is fundamental to graph analytics and has wide applications. Unfortunately, high computational complexity limits the robustness guarantees of existing algorithms: they do not ...