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Backdoor attacks represent a serious threat to neural network models.
Random graphs
E. N. Gilbert · 1959
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A (sub)graph isomorphism algorithm for matching large graphs
L. P. Cordella, P. Foggia, C. Sansone, and M. Vento · 2004
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P. Sen, G. Namata, M. Bilgic, L. Getoor, B. Gallagher, and T. Eliassi-Rad · 2008
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Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
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"why should I trust you?": Explaining the predictions of any classifier
M. T. Ribeiro, S. Singh, and C. Guestrin · 2016
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Inductive representation learning on large graphs
W. L. Hamilton, Z. Ying, and J. Leskovec · 2017
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Semi-supervised classification with graph convolutional networks
T. N. Kipf and M. Welling · 2017
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Axiomatic attribution for deep networks
M. Sundararajan, A. Taly, and Q. Yan · 2017
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Trojaning attack on neural networks
Y. Liu, S. Ma, Y. Aafer, W. Lee, J. Zhai, W. Wang, and X. Zhang · 2018
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Graph Attention Networks
P. Veličković, G. Cucurull, A. Casanova, A. Romero, P. Liò, and Y. Bengio · 2018
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Hierarchical graph representation learning with differentiable pooling
Z. Ying, J. You, C. Morris, X. Ren, W. L. Hamilton, and J. Leskovec · 2018
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An end-to-end deep learning architecture for graph classification
M. Zhang, Z. Cui, M. Neumann, and Y. Chen · 2018
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Explaining deep neural networks with a polynomial time algorithm for shapley value approximation
M. Ancona, C. Oztireli, and M. Gross · 2019
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Gnnexplainer: Generating explanations for graph neural networks
Z. Ying, D. Bourgeois, J. You, M. Zitnik, and J. Leskovec · 2019
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Graphlime: Local interpretable model explanations for graph neural networks
Q. Huang, M. Yamada, Y. Tian, D. Singh, D. Yin, and Y. Chang · 2020
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Invisible backdoor attacks on deep neural networks via steganography and regularization
S. Li, M. Xue, B. Zhao, H. Zhu, and X. Zhang · 2020
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Tudataset: A collection of benchmark datasets for learning with graphs
C. Morris, N. M. Kriege, F. Bause, K. Kersting, P. Mutzel, and M. Neumann · 2020
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Backdoor attacks to graph neural networks, 2020
Z. Zhang, J. Jia, B. Wang, and N. Z. Gong · 2020
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M. Weber, G. Domeniconi, J. Chen, D. K. I. Weidele, C. Bellei, T. Robinson, and C. E. Leiserson · 2019
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How powerful are graph neural networks?
K. Xu, W. Hu, J. Leskovec, and S. Jegelka · 2019
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A comprehensive survey on graph neural networks
Z. Wu, S. Pan, F. Chen, G. Long, C. Zhang, and P. S. Yu · 2021
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Z. Xi, R. Pang, S. Ji, and T. Wang · 2021
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