Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Exploratory Adversarial Attacks on Graph Neural Networks for Semi-Supervised Node Classification
Xixun Lin, Chuan Zhou, Jia Wu, et al.
Pattern Recognition (2022) Vol. 133, pp. 109042-109042
Closed Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

Collaborative contrastive learning for hypergraph node classification
Hanrui Wu, Nuosi Li, Jia Zhang, et al.
Pattern Recognition (2023) Vol. 146, pp. 109995-109995
Closed Access | Times Cited: 21
Multi-dimensional Graph Neural Network for Sequential Recommendation
Yongjing Hao, Jun Ma, Pengpeng Zhao, et al.
Pattern Recognition (2023) Vol. 139, pp. 109504-109504
Closed Access | Times Cited: 18
Multi-target label backdoor attacks on graph neural networks
Kaiyang Wang, Huaxin Deng, Yijia Xu, et al.
Pattern Recognition (2024) Vol. 152, pp. 110449-110449
Closed Access | Times Cited: 6
Improving Augmentation Consistency for Graph Contrastive Learning
Weixin Bu, Xiaofeng Cao, Yizhen Zheng, et al.
Pattern Recognition (2023) Vol. 148, pp. 110182-110182
Closed Access | Times Cited: 13
Transferable graph auto-encoders for cross-network node classification
Hanrui Wu, Lei Tian, Yanxin Wu, et al.
Pattern Recognition (2024) Vol. 150, pp. 110334-110334
Closed Access | Times Cited: 5
Focus on informative graphs! Semi-supervised active learning for graph-level classification
Wei Ju, Zhengyang Mao, Ziyue Qiao, et al.
Pattern Recognition (2024) Vol. 153, pp. 110567-110567
Closed Access | Times Cited: 5
Self-attention empowered graph convolutional network for structure learning and node embedding
Mengying Jiang, Guizhong Liu, Yuanchao Su, et al.
Pattern Recognition (2024) Vol. 153, pp. 110537-110537
Open Access | Times Cited: 5
GANN: Graph Alignment Neural Network for semi-supervised learning
Linxuan Song, Wenxuan Tu, Sihang Zhou, et al.
Pattern Recognition (2024) Vol. 154, pp. 110484-110484
Open Access | Times Cited: 4
Graph Geometric Algebra networks for graph representation learning
Jianqi Zhong, Wenming Cao
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
SPA: A poisoning attack framework for graph neural networks through searching and pairing
Xiao Liu, Junjie Huang, Wentao Zhao, et al.
Machine Learning (2025) Vol. 114, Iss. 1
Open Access
Rethinking the robustness of Graph Neural Networks: An information theory perspective
Ding Li, Hui Xia, Xin Li, et al.
Knowledge-Based Systems (2025), pp. 113221-113221
Closed Access
Momentum gradient-based untargeted poisoning attack on hypergraph neural networks
Yang Chen, Stjepan Picek, Zhonglin Ye, et al.
Neurocomputing (2025), pp. 129835-129835
Closed Access
Enhancing graph representation learning via type-aware decoupling and node influence allocation
Guo-Chang Zhu, Jun Hu, Li Liu, et al.
Applied Intelligence (2025) Vol. 55, Iss. 6
Closed Access
SPEAR: A Structure-Preserving Manipulation Method for Graph Backdoor Attacks
Yuanhao Ding, Yang Liu, Yugang Ji, et al.
(2025), pp. 1237-1247
Closed Access
Long-tailed graph neural networks via graph structure learning for node classification
Junchao Lin, Yuan Wan, Jingwen Xu, et al.
Applied Intelligence (2023) Vol. 53, Iss. 17, pp. 20206-20222
Closed Access | Times Cited: 7
Robustness and Transferability of Adversarial Attacks on Different Image Classification Neural Networks
Kamilya Smagulova, Lina Bacha, Mohammed E. Fouda, et al.
Electronics (2024) Vol. 13, Iss. 3, pp. 592-592
Open Access | Times Cited: 2
GCIA: A Black-Box Graph Injection Attack Method Via Graph Contrastive Learning
Xiao Liu, Junjie Huang, Wentao Zhao
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2024), pp. 6570-6574
Closed Access | Times Cited: 2
Node Injection Attack Based on Label Propagation Against Graph Neural Network
Peican Zhu, Zhengyan Pan, Keke Tang, et al.
IEEE Transactions on Computational Social Systems (2024), pp. 1-13
Open Access | Times Cited: 2
Classification optimization node injection attack on graph neural networks
Mingda Ma, Hui Xia, Xin Li, et al.
Knowledge-Based Systems (2024) Vol. 301, pp. 112323-112323
Closed Access | Times Cited: 2
Defending adversarial attacks in Graph Neural Networks via tensor enhancement
Jianfu Zhang, Hong Yan, Dawei Cheng, et al.
Pattern Recognition (2024) Vol. 158, pp. 110954-110954
Closed Access | Times Cited: 2
Localized curvature-based combinatorial subgraph sampling for large-scale graphs
Dong Wook Shu, Youjin Kim, Junseok Kwon
Pattern Recognition (2023) Vol. 139, pp. 109475-109475
Closed Access | Times Cited: 5
Uncovering Hidden Vulnerabilities in Convolutional Neural Networks through Graph-based Adversarial Robustness Evaluation
Ke Wang, Zicong Chen, Xilin Dang, et al.
Pattern Recognition (2023) Vol. 143, pp. 109745-109745
Closed Access | Times Cited: 5
Self-supervised robust Graph Neural Networks against noisy graphs and noisy labels
Jinliang Yuan, Hualei Yu, Meng Cao, et al.
Applied Intelligence (2023) Vol. 53, Iss. 21, pp. 25154-25170
Closed Access | Times Cited: 4
Improving Variational Graph Autoencoders With Multi-Order Graph Convolutions
Lining Yuan, Ping Jiang, Wen Zhu, et al.
IEEE Access (2024) Vol. 12, pp. 46919-46929
Open Access | Times Cited: 1
An effective targeted label adversarial attack on graph neural networks by strategically allocating the attack budget
Feilong Cao, Q. Chen, Hailiang Ye
Knowledge-Based Systems (2024) Vol. 293, pp. 111689-111689
Closed Access | Times Cited: 1
Page 1 - Next Page

Scroll to top