JAMN-GNN: jointly-adversarial graph neural network for noisy labels and missing attributes

Guangliang ZHAO; Yulin LIU; Anchen LI; Ping ZHANG; Xueyan LIU; Yan ZHANG; Riting XIA

doi:10.1007/s11704-026-51545-7

Front. Comput. Sci. ›› 2027, Vol. 21 ›› Issue (3) :2103330 DOI: 10.1007/s11704-026-51545-7

Artificial Intelligence

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JAMN-GNN: jointly-adversarial graph neural network for noisy labels and missing attributes

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Guangliang ZHAO, Yulin LIU, Anchen LI, Ping ZHANG, Xueyan LIU, Yan ZHANG, Riting XIA. JAMN-GNN: jointly-adversarial graph neural network for noisy labels and missing attributes. Front. Comput. Sci., 2027, 21(3): 2103330 DOI:10.1007/s11704-026-51545-7

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References

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[1]	Li M, Chen J, Yu C, Jiang G, Zhang R, Shen Y, Song H H . Topology-driven attribute recovery for attribute missing graph learning in social internet of things. IEEE Internet of Things Journal, 2025, 12( 11): 16298–16313

[2]	Peng X, Cheng J, Tang X, Zhang B, Tu W . Multi-view graph imputation network. Information Fusion, 2024, 102: 102024

[3]	Peng X, Cheng J, Tang X, Deng Z, Tu W, Xiong N . HSNet: An intelligent hierarchical semantic-aware network system for real-time semantic segmentation. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024, 54( 7): 4318–4330

[4]	Velickovic P, Cucurull G, Casanova A, Romero A, Liò P, Bengio Y. Graph attention networks. In: Proceedings of the 6th International Conference on Learning Representations. 2018

[5]	Laine S, Aila T. Temporal ensembling for semi-supervised learning. In: Proceedings of the 5th International Conference on Learning Representations. 2017

[6]	Pei H, Xiong Y, Wang P, Tao J, Liu J, Deng H, Ma J, Guan X. Memory disagreement: a pseudo-labeling measure from training dynamics for semi-supervised graph learning. In: Proceedings of the ACM Web Conference 2024. 2024, 434−445

[7]	Wang Z, Sun D, Zhou S, Wang H, Fan J, Huang L, Bu J. NoisyGL: a comprehensive benchmark for graph neural networks under label noise. In: Proceedings of the 38th International Conference on Neural Information Processing Systems. 2024, 1206