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 ...
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
Exploring the biomedical interactions about chemical compounds and protein targets is crucial for drug discovery. Determining these interactions (DDI/DTI) not only reveals the potential synergistic ...
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