Fetching the paper…
Reading the bibliography…
Graph Neural Networks (GNNs) have boosted the performance for many graph-related tasks.
Data mining: concepts and techniques
Jiawei Han, Jian Pei, and Micheline Kamber · 2011
Earlier work this paper cites.
Explaining and harnessing adversarial examples
Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
Earlier work this paper cites.
" why should i trust you?" explaining the predictions of any classifier
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin · 2016
Earlier work this paper cites.
Learning deep features for discriminative localization
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, and Antonio Torralba · 2016
Earlier work this paper cites.
Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2017
Earlier work this paper cites.
Inductive representation learning on large graphs
Will Hamilton, Zhitao Ying, and Jure Leskovec · 2017
Earlier work this paper cites.
Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
Earlier work this paper cites.
Deep modeling of social relations for recommendation
Wenqi Fan, Qing Li, and Min Cheng · 2018
Earlier work this paper cites.
Graph-to-sequence learning using gated graph neural networks
Daniel Beck, Gholamreza Haffari, and Trevor Cohn · 2018
Earlier work this paper cites.
Adversarial attacks on neural networks for graph data
Daniel Zügner, Amir Akbarnejad, and Stephan Günnemann · 2018
Earlier work this paper cites.
Adversarial attack on graph structured data
Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, and Le Song · 2018
Earlier work this paper cites.
Adversarial detection with model interpretation
Ninghao Liu, Hongxia Yang, and Xia Hu · 2018
Earlier work this paper cites.
Graph neural networks for social recommendation
Wenqi Fan, Yao Ma, Qing Li, Yuan He, Eric Zhao, Jiliang Tang, and Dawei Yin · 2019
Earlier work this paper cites.
Deep adversarial social recommendation
Wenqi Fan, Tyler Derr, Yao Ma, Jianping Wang, Jiliang Tang, and Qing Li · 2019
Earlier work this paper cites.
Deep social collaborative filtering
Wenqi Fan, Yao Ma, Dawei Yin, Jianping Wang, Jiliang Tang, and Qing Li · 2019
Earlier work this paper cites.
Does gender matter? towards fairness in dialogue systems
Haochen Liu, Jamell Dacon, Wenqi Fan, Hui Liu, Zitao Liu, and Jiliang Tang · 2019
Earlier work this paper cites.
Attacking graph-based classification via manipulating the graph structure
Binghui Wang and Neil Zhenqiang Gong · 2019
Cited alongside, same era.
Adversarial examples for graph data: deep insights into attack and defense
Huijun Wu, Chen Wang, Yuriy Tyshetskiy, Andrew Docherty, Kai Lu, and Liming Zhu · 2019
Cited alongside, same era.
Topology attack and defense for graph neural networks: an optimization perspective
Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, and Xue Lin · 2019
Cited alongside, same era.
Gnnexplainer: Generating explanations for graph neural networks
Zhitao Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, and Jure Leskovec · 2019
Cited alongside, same era.
Adversarial attacks on graph neural networks via meta learning
Daniel Zügner and Stephan Günnemann · 2019
Cited alongside, same era.
Interpretation of neural networks is fragile
Self-supervised learning on graphs: Deep insights and new direction
Wei Jin, Tyler Derr, Haochen Liu, Yiqi Wang, Suhang Wang, Zitao Liu, and Jiliang Tang · 2020
Later among the works it cites.
Towards more practical adversarial attacks on graph neural networks
Jiaqi Ma, Shuangrui Ding, and Qiaozhu Mei · 2020
Later among the works it cites.
A restricted black-box adversarial framework towards attacking graph embedding models
Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang, Honglei Zhang, Peng Cui, Wenwu Zhu, and Junzhou Huang · 2020
Later among the works it cites.
Pgm-explainer: Probabilistic graphical model explanations for graph neural networks
M Vu and MT Thai · 2020
Later among the works it cites.
Interpretation of nlp models through input marginalization
Siwon Kim, Jihun Yi, Eunji Kim, and Sungroh Yoon · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Amirata Ghorbani, Abubakar Abid, and James Zou · 2019
Cited alongside, same era.
Fooling neural network interpretations via adversarial model manipulation
Juyeon Heo, Sunghwan Joo, and Taesup Moon · 2019
Cited alongside, same era.
Heterogeneous graph attention network
Xiao Wang, Houye Ji, Chuan Shi, Bai Wang, Yanfang Ye, Peng Cui, and Philip S Yu · 2019
Cited alongside, same era.
Attacking graph convolutional networks via rewiring
Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, and Jiliang Tang · 2019
Cited alongside, same era.
Epidemic graph convolutional network
Tyler Derr, Yao Ma, Wenqi Fan, Xiaorui Liu, Charu Aggarwal, and Jiliang Tang · 2020
Cited alongside, same era.
A graph neural network framework for social recommendations
Wenqi Fan, Yao Ma, Qing Li, Jianping Wang, Guoyong Cai, Jiliang Tang, and Dawei Yin · 2020
Cited alongside, same era.
Adversarial attacks and defenses in images, graphs and text: A review
Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, and Anil K Jain · 2020
Cited alongside, same era.
Attacking graph-based classification without changing existing connections
Xuening Xu, Xiaojiang Du, and Qiang Zeng · 2020
Later among the works it cites.
Am-gcn: Adaptive multi-channel graph convolutional networks
Xiao Wang, Meiqi Zhu, Deyu Bo, Peng Cui, Chuan Shi, and Jian Pei · 2020
Later among the works it cites.
Deeprobust: A pytorch library for adversarial attacks and defenses
Yaxin Li, Wei Jin, Han Xu, and Jiliang Tang · 2020
Later among the works it cites.
Graph structure learning for robust graph neural networks
Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, and Jiliang Tang · 2020
Later among the works it cites.
Node similarity preserving graph convolutional networks
Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, and Jiliang Tang · 2021
Closest in time.
Attacking black-box recommendations via copying cross-domain user profiles
Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, and Qing Li · 2021
Closest in time.
Adversarial attacks and defenses on graphs
Wei Jin, Yaxing Li, Han Xu, Yiqi Wang, Shuiwang Ji, Charu Aggarwal, and Jiliang Tang · 2021
Closest in time.
Elastic graph neural networks
Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, and Jiliang Tang · 2021
Closest in time.
Trustworthy ai: A computational perspective
Haochen Liu, Yiqi Wang, Wenqi Fan, Xiaorui Liu, Yaxin Li, Shaili Jain, Anil K Jain, and Jiliang Tang · 2021
Closest in time.
On explainability of graph neural networks via subgraph explorations
Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, and Shuiwang Ji · 2021
Closest in time.