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GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models.

, , , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 5694-5703. PMLR, (2018)

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Representation Learning on Graphs: Methods and Applications, , and . arXiv:1709.05584 cs, (April 2018)arXiv: 1709.05584.Neural Execution of Graph Algorithms., , , , and . ICLR, OpenReview.net, (2020)Hyperbolic Graph Topic Modeling Network with Continuously Updated Topic Tree., , and . KDD, page 3206-3216. ACM, (2023)Adversarially Robust Neural Architecture Search for Graph Neural Networks., , , , , , , and . CVPR, page 8143-8152. IEEE, (2023)How Powerful is Implicit Denoising in Graph Neural Networks., , , , , and . CoRR, (2022)Fea2Fea: Exploring Structural Feature Correlations via Graph Neural Networks., and . PKDD/ECML Workshops (1), volume 1524 of Communications in Computer and Information Science, page 238-257. Springer, (2021)Redundancy-Free Computation for Graph Neural Networks., , , , , and . KDD, page 997-1005. ACM, (2020)HiPool: Modeling Long Documents Using Graph Neural Networks., , , and . ACL (2), page 161-171. Association for Computational Linguistics, (2023)TrustLLM: Trustworthiness in Large Language Models., , , , , , , , , and 56 other author(s). CoRR, (2024)Hypformer: Exploring Efficient Hyperbolic Transformer Fully in Hyperbolic Space., , , , , and . CoRR, (2024)