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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 Unifying Generative Model for Graph Learning Algorithms: Label Propagation, Graph Convolutions, and Combinations
Junteng Jia, Austin R. Benson
SIAM Journal on Mathematics of Data Science (2022) Vol. 4, Iss. 1, pp. 100-125
Open Access | Times Cited: 14

Showing 14 citing articles:

A graph neural network (GNN) approach to basin-scale river network learning: the role of physics-based connectivity and data fusion
Alexander Y. Sun, Peishi Jiang, Zong‐Liang Yang, et al.
Hydrology and earth system sciences (2022) Vol. 26, Iss. 19, pp. 5163-5184
Open Access | Times Cited: 42
Is Homophily a Necessity for Graph Neural Networks?
Yao Ma, Xiaorui Liu, Neil Shah, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 54
Towards an Optimal Asymmetric Graph Structure for Robust Semi-supervised Node Classification
Zixing Song, Yifei Zhang, Irwin King
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2022), pp. 1656-1665
Closed Access | Times Cited: 23
Learning structure perception MLPs on graphs: a layer-wise graph knowledge distillation framework
Hangyuan Du, Rong Yu, Liang Bai, et al.
International Journal of Machine Learning and Cybernetics (2024) Vol. 15, Iss. 10, pp. 4357-4372
Closed Access | Times Cited: 5
Nonlinear Correct and Smooth for Graph-Based Semi-Supervised Learning
Yuanhang Shao, Xiuwen Liu
ACM Transactions on Knowledge Discovery from Data (2025)
Closed Access
Random Fields in Physics, Biology and Data Science
Enrique Hernández-Lemus
Frontiers in Physics (2021) Vol. 9
Open Access | Times Cited: 16
Multitemporal hyperspectral satellite image analysis and classification using fast scale invariant feature transform and deep learning neural network classifier
G. Vinuja, N. Bharatha Devi
Earth Science Informatics (2023) Vol. 16, Iss. 1, pp. 877-886
Closed Access | Times Cited: 5
Nonlinear Correct and Smooth for Semi-Supervised Learning
Yuanhang Shao, Xiuwen Liu
2022 International Joint Conference on Neural Networks (IJCNN) (2024) Vol. 33, pp. 1-8
Closed Access | Times Cited: 1
Unifying Node Labels, Features, and Distances for Deep Network Completion
Qiang Wei, Guangmin Hu
Entropy (2021) Vol. 23, Iss. 6, pp. 771-771
Open Access | Times Cited: 6
Quantum-inspired measures of network distinguishability
Athanasia Polychronopoulou, Jumanah Alshehri, Zoran Obradović
Social Network Analysis and Mining (2023) Vol. 13, Iss. 1
Closed Access | Times Cited: 1
Graph Belief Propagation Networks
Junteng Jia, Cenk Baykal, Vamsi K. Potluru, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 2
Learning Label Initialization for Time-Dependent Harmonic Extension.
Amitoz Azad
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (2022), pp. 2791-2797
Open Access | Times Cited: 1
A nonlinear diffusion method for semi-supervised learning on hypergraphs
Francesco Tudisco, Konstantin Prokopchik, Austin R. Benson
arXiv (Cornell University) (2021)
Closed Access
Random Graph-Based Neuromorphic Learning with a Layer-Weaken Structure
Ruiqi Mao, Rongxin Cui
arXiv (Cornell University) (2021)
Open Access
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