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A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection


May 23, 2022
Bingzhe Wu, Jintang Li, Junchi Yu, Yatao Bian, Hengtong Zhang, CHaochao Chen, Chengbin Hou, Guoji Fu, Liang Chen, Tingyang Xu, Yu Rong, Xiaolin Zheng, Junzhou Huang, Ran He, Baoyuan Wu, GUangyu Sun, Peng Cui, Zibin Zheng, Zhe Liu, Peilin Zhao

* Preprint; Work in progress. arXiv admin note: substantial text overlap with arXiv:2202.07114 

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Understanding Knowledge Integration in Language Models with Graph Convolutions


Feb 15, 2022
Yifan Hou, Guoji Fu, Mrinmaya Sachan

* Code is available: https://github.com/yifan-h/GCS_KI 

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Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift


Feb 15, 2022
Bingzhe Wu, Jintang Li, Chengbin Hou, Guoji Fu, Yatao Bian, Liang Chen, Junzhou Huang


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$p$-Laplacian Based Graph Neural Networks


Nov 14, 2021
Guoji Fu, Peilin Zhao, Yatao Bian


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Robust Dynamic Network Embedding via Ensembles


May 30, 2021
Chengbin Hou, Guoji Fu, Peng Yang, Shan He, Ke Tang


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Understanding Graph Neural Networks from Graph Signal Denoising Perspectives


Jun 08, 2020
Guoji Fu, Yifan Hou, Jian Zhang, Kaili Ma, Barakeel Fanseu Kamhoua, James Cheng

* 19 pages, 8 figures 

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Learning Topological Representation for Networks via Hierarchical Sampling


Feb 15, 2019
Guoji Fu, Chengbin Hou, Xin Yao


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Representation Learning for Heterogeneous Information Networks via Embedding Events


Jan 29, 2019
Guoji Fu, Bo Yuan, Qiqi Duan, Xin Yao


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