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OpenAlex Citation Counts

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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:

A Comprehensive Survey on Graph Neural Networks
Zonghan Wu, Shirui Pan, Fengwen Chen, et al.
IEEE Transactions on Neural Networks and Learning Systems (2020) Vol. 32, Iss. 1, pp. 4-24
Open Access | Times Cited: 3364

Showing 1-25 of 3364 citing articles:

Graph neural networks: A review of methods and applications
Jie Zhou, Ganqu Cui, Shengding Hu, et al.
AI Open (2020) Vol. 1, pp. 57-81
Open Access | Times Cited: 3796
Deep Learning for Generic Object Detection: A Survey
Li Liu, Wanli Ouyang, Xiaogang Wang, et al.
International Journal of Computer Vision (2019) Vol. 128, Iss. 2, pp. 261-318
Open Access | Times Cited: 2378
Graph WaveNet for Deep Spatial-Temporal Graph Modeling
Zonghan Wu, Shirui Pan, Guodong Long, et al.
(2019), pp. 1907-1913
Open Access | Times Cited: 1701
ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope
Partha Pratim Ray
Internet of Things and Cyber-Physical Systems (2023) Vol. 3, pp. 121-154
Open Access | Times Cited: 1488
Simplifying Graph Convolutional Networks
Felix Wu, Tianyi Zhang, Amauri H. Souza, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 1170
Graph Neural Networks: A Review of Methods and Applications
Jie Zhou, Ganqu Cui, Shengding Hu, et al.
arXiv (Cornell University) (2018)
Open Access | Times Cited: 1160
Graph convolutional networks: a comprehensive review
Si Zhang, Hanghang Tong, Jiejun Xu, et al.
Computational Social Networks (2019) Vol. 6, Iss. 1
Open Access | Times Cited: 1149
DeepGCNs: Can GCNs Go As Deep As CNNs?
Guohao Li, Matthias Müller, Ali Thabet, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2019)
Open Access | Times Cited: 1113
GMAN: A Graph Multi-Attention Network for Traffic Prediction
Chuanpan Zheng, Xiaoliang Fan, Cheng Wang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2020) Vol. 34, Iss. 01, pp. 1234-1241
Open Access | Times Cited: 1089
Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition
Ziyu Liu, Hongwen Zhang, Zhenghao Chen, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020), pp. 140-149
Open Access | Times Cited: 880
Knowledge Graphs
Aidan Hogan, Eva Blomqvist, Michael Cochez, et al.
ACM Computing Surveys (2021) Vol. 54, Iss. 4, pp. 1-37
Open Access | Times Cited: 863
Deep Closest Point: Learning Representations for Point Cloud Registration
Yue Wang, Justin Solomon
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2019), pp. 3522-3531
Open Access | Times Cited: 811
Graph neural network for traffic forecasting: A survey
Weiwei Jiang, Jiayun Luo
Expert Systems with Applications (2022) Vol. 207, pp. 117921-117921
Open Access | Times Cited: 765
Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud
Weijing Shi, Raj Rajkumar
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020), pp. 1708-1716
Open Access | Times Cited: 731
Graph Neural Networks in Recommender Systems: A Survey
Shiwen Wu, Fei Sun, Wentao Zhang, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 5, pp. 1-37
Open Access | Times Cited: 657
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks
Minjie Wang, Da Zheng, Zihao Ye, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 654
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
Yu Rong, Wenbing Huang, Tingyang Xu, et al.
arXiv (Cornell University) (2019)
Open Access | Times Cited: 544
An Introductory Review of Deep Learning for Prediction Models With Big Data
Frank Emmert‐Streib, Zhen Yang, Feng Han, et al.
Frontiers in Artificial Intelligence (2020) Vol. 3
Open Access | Times Cited: 516
Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting
Lei Bai, Lina Yao, Can Li, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 512
Medical image segmentation using deep learning: A survey
Risheng Wang, Tao Lei, Ruixia Cui, et al.
IET Image Processing (2022) Vol. 16, Iss. 5, pp. 1243-1267
Open Access | Times Cited: 438
Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation
Xin Xia, Hongzhi Yin, Junliang Yu, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2021) Vol. 35, Iss. 5, pp. 4503-4511
Open Access | Times Cited: 433
Attributed Graph Clustering: A Deep Attentional Embedding Approach
Chun Wang, Shirui Pan, Ruiqi Hu, et al.
(2019), pp. 3670-3676
Open Access | Times Cited: 413
A Comprehensive Survey on Graph Anomaly Detection With Deep Learning
Xiaoxiao Ma, Jia Wu, Shan Xue, et al.
IEEE Transactions on Knowledge and Data Engineering (2021) Vol. 35, Iss. 12, pp. 12012-12038
Open Access | Times Cited: 413
Atomistic Line Graph Neural Network for improved materials property predictions
Kamal Choudhary, Brian DeCost
npj Computational Materials (2021) Vol. 7, Iss. 1
Open Access | Times Cited: 408
AM-GCN: Adaptive Multi-channel Graph Convolutional Networks
Xiao Wang, Meiqi Zhu, Deyu Bo, et al.
(2020), pp. 1243-1253
Open Access | Times Cited: 398
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