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Energy-based Out-of-Distribution Detection for Graph Neural Networks., , , and . ICLR, OpenReview.net, (2023)How Graph Neural Networks Learn: Lessons from Training Dynamics in Function Space., , , , and . CoRR, (2023)Advective Diffusion Transformers for Topological Generalization in Graph Learning., , , , , and . CoRR, (2023)Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach., , and . NeurIPS, page 19435-19447. (2021)Trading Hard Negatives and True Negatives: A Debiased Contrastive Collaborative Filtering Approach., , , , , and . IJCAI, page 2355-2361. ijcai.org, (2022)Graph Out-of-Distribution Generalization via Causal Intervention., , , , and . WWW, page 850-860. ACM, (2024)Simplifying and Empowering Transformers for Large-Graph Representations., , , , , , , and . CoRR, (2023)GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks., , , and . KDD, page 3525-3536. ACM, (2023)Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs., , , and . ICLR, OpenReview.net, (2023)A Chaotic Image Encryption Scheme Based on Genetic Central Dogma and KMP Method., , , , and . Int. J. Bifurc. Chaos, 32 (12): 2250186:1-2250186:23 (2022)