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:
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
He Zhang, Bang Ye Wu, Xingliang Yuan, et al.
arXiv (Cornell University) (2022)
Open Access | Times Cited: 35
He Zhang, Bang Ye Wu, Xingliang Yuan, et al.
arXiv (Cornell University) (2022)
Open Access | Times Cited: 35
Showing 1-25 of 35 citing articles:
Unifying Large Language Models and Knowledge Graphs: A Roadmap
Shirui Pan, Linhao Luo, Yufei Wang, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 62
Shirui Pan, Linhao Luo, Yufei Wang, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 62
Trustworthy Recommender Systems
Shoujin Wang, Xiuzhen Zhang, Yan Wang, et al.
ACM Transactions on Intelligent Systems and Technology (2023) Vol. 15, Iss. 4, pp. 1-20
Open Access | Times Cited: 38
Shoujin Wang, Xiuzhen Zhang, Yan Wang, et al.
ACM Transactions on Intelligent Systems and Technology (2023) Vol. 15, Iss. 4, pp. 1-20
Open Access | Times Cited: 38
Multimodal data integration for oncology in the era of deep neural networks: a review
Asim Waqas, Aakash Tripathi, Ravi P. Ramachandran, et al.
Frontiers in Artificial Intelligence (2024) Vol. 7
Open Access | Times Cited: 18
Asim Waqas, Aakash Tripathi, Ravi P. Ramachandran, et al.
Frontiers in Artificial Intelligence (2024) Vol. 7
Open Access | Times Cited: 18
Multivariate Time Series Forecasting With Dynamic Graph Neural ODEs
Ming Jin, Yu Zheng, Yuan-Fang Li, et al.
IEEE Transactions on Knowledge and Data Engineering (2022) Vol. 35, Iss. 9, pp. 9168-9180
Open Access | Times Cited: 61
Ming Jin, Yu Zheng, Yuan-Fang Li, et al.
IEEE Transactions on Knowledge and Data Engineering (2022) Vol. 35, Iss. 9, pp. 9168-9180
Open Access | Times Cited: 61
Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
Yixin Liu, Yizhen Zheng, Daokun Zhang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2023) Vol. 37, Iss. 4, pp. 4516-4524
Open Access | Times Cited: 30
Yixin Liu, Yizhen Zheng, Daokun Zhang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2023) Vol. 37, Iss. 4, pp. 4516-4524
Open Access | Times Cited: 30
A survey on fairness-aware recommender systems
Di Jin, Luzhi Wang, He Zhang, et al.
Information Fusion (2023) Vol. 100, pp. 101906-101906
Open Access | Times Cited: 25
Di Jin, Luzhi Wang, He Zhang, et al.
Information Fusion (2023) Vol. 100, pp. 101906-101906
Open Access | Times Cited: 25
Graph spatiotemporal process for multivariate time series anomaly detection with missing values
Yu Zheng, Huan Yee Koh, Ming Jin, et al.
Information Fusion (2024) Vol. 106, pp. 102255-102255
Open Access | Times Cited: 7
Yu Zheng, Huan Yee Koh, Ming Jin, et al.
Information Fusion (2024) Vol. 106, pp. 102255-102255
Open Access | Times Cited: 7
Learning Strong Graph Neural Networks with Weak Information
Yixin Liu, Kaize Ding, Jianling Wang, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2023), pp. 1559-1571
Open Access | Times Cited: 17
Yixin Liu, Kaize Ding, Jianling Wang, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2023), pp. 1559-1571
Open Access | Times Cited: 17
Correlation-Aware Spatial–Temporal Graph Learning for Multivariate Time-Series Anomaly Detection
Yu Zheng, Huan Yee Koh, Ming Jin, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 9, pp. 11802-11816
Open Access | Times Cited: 15
Yu Zheng, Huan Yee Koh, Ming Jin, et al.
IEEE Transactions on Neural Networks and Learning Systems (2023) Vol. 35, Iss. 9, pp. 11802-11816
Open Access | Times Cited: 15
Jointly Attacking Graph Neural Network and its Explanations
Wenqi Fan, Han Xu, Wei Jin, et al.
2022 IEEE 38th International Conference on Data Engineering (ICDE) (2023), pp. 654-667
Open Access | Times Cited: 14
Wenqi Fan, Han Xu, Wei Jin, et al.
2022 IEEE 38th International Conference on Data Engineering (ICDE) (2023), pp. 654-667
Open Access | Times Cited: 14
Beyond Low-Pass Filtering: Graph Convolutional Networks With Automatic Filtering
Zonghan Wu, Shirui Pan, Guodong Long, et al.
IEEE Transactions on Knowledge and Data Engineering (2022) Vol. 35, Iss. 7, pp. 6687-6697
Open Access | Times Cited: 20
Zonghan Wu, Shirui Pan, Guodong Long, et al.
IEEE Transactions on Knowledge and Data Engineering (2022) Vol. 35, Iss. 7, pp. 6687-6697
Open Access | Times Cited: 20
Contrastive Graph Similarity Networks
Luzhi Wang, Yizhen Zheng, Di Jin, et al.
ACM Transactions on the Web (2023) Vol. 18, Iss. 2, pp. 1-20
Open Access | Times Cited: 7
Luzhi Wang, Yizhen Zheng, Di Jin, et al.
ACM Transactions on the Web (2023) Vol. 18, Iss. 2, pp. 1-20
Open Access | Times Cited: 7
Projective Ranking-based GNN Evasion Attacks
He Zhang, Xingliang Yuan, Chuan Zhou, et al.
IEEE Transactions on Knowledge and Data Engineering (2022), pp. 1-14
Open Access | Times Cited: 10
He Zhang, Xingliang Yuan, Chuan Zhou, et al.
IEEE Transactions on Knowledge and Data Engineering (2022), pp. 1-14
Open Access | Times Cited: 10
GraphGuard: Detecting and Counteracting Training Data Misuse in Graph Neural Networks
Bang Ye Wu, He Zhang, Xiangwen Yang, et al.
(2024)
Open Access | Times Cited: 1
Bang Ye Wu, He Zhang, Xiangwen Yang, et al.
(2024)
Open Access | Times Cited: 1
GOODAT: Towards Test-Time Graph Out-of-Distribution Detection
Luzhi Wang, Dongxiao He, He Zhang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 14, pp. 15537-15545
Open Access | Times Cited: 1
Luzhi Wang, Dongxiao He, He Zhang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 14, pp. 15537-15545
Open Access | Times Cited: 1
Migrate demographic group for fair Graph Neural Networks
Yanming Hu, Tianchi Liao, Jialong Chen, et al.
Neural Networks (2024) Vol. 175, pp. 106264-106264
Closed Access | Times Cited: 1
Yanming Hu, Tianchi Liao, Jialong Chen, et al.
Neural Networks (2024) Vol. 175, pp. 106264-106264
Closed Access | Times Cited: 1
Securing Graph Neural Networks in MLaaS: A Comprehensive Realization of Query-based Integrity Verification
Bang Ye Wu, Xingliang Yuan, Shuo Wang, et al.
2022 IEEE Symposium on Security and Privacy (SP) (2024) Vol. 52, pp. 2534-2552
Closed Access | Times Cited: 1
Bang Ye Wu, Xingliang Yuan, Shuo Wang, et al.
2022 IEEE Symposium on Security and Privacy (SP) (2024) Vol. 52, pp. 2534-2552
Closed Access | Times Cited: 1
A Survey of Graph Neural Networks for Social Recommender Systems
Kartik Sharma, Yeon-Chang Lee, Sivagami Nambi, et al.
arXiv (Cornell University) (2022)
Open Access | Times Cited: 8
Kartik Sharma, Yeon-Chang Lee, Sivagami Nambi, et al.
arXiv (Cornell University) (2022)
Open Access | Times Cited: 8
Beyond-accuracy: a review on diversity, serendipity, and fairness in recommender systems based on graph neural networks
Tomislav Đuričić, Dominik Kowald, Emanuel Lacić, et al.
Frontiers in Big Data (2023) Vol. 6
Open Access | Times Cited: 4
Tomislav Đuričić, Dominik Kowald, Emanuel Lacić, et al.
Frontiers in Big Data (2023) Vol. 6
Open Access | Times Cited: 4
Multi-Relational Graph Neural Architecture Search with Fine-grained Message Passing
Xin Zheng, Miao Zhang, Chunyang Chen, et al.
2021 IEEE International Conference on Data Mining (ICDM) (2022), pp. 783-792
Closed Access | Times Cited: 7
Xin Zheng, Miao Zhang, Chunyang Chen, et al.
2021 IEEE International Conference on Data Mining (ICDM) (2022), pp. 783-792
Closed Access | Times Cited: 7
A Survey on Fairness-Aware Recommender Systems
Di Jin, Luzhi Wang, He Zhang, et al.
(2023)
Open Access | Times Cited: 3
Di Jin, Luzhi Wang, He Zhang, et al.
(2023)
Open Access | Times Cited: 3
Semantic Interpretation and Validation of Graph Attention-Based Explanations for GNN Models
Efimia Panagiotaki, Daniele De Martini, Lars Kunze
(2023), pp. 375-380
Open Access | Times Cited: 3
Efimia Panagiotaki, Daniele De Martini, Lars Kunze
(2023), pp. 375-380
Open Access | Times Cited: 3
Unifying Graph Contrastive Learning with Flexible Contextual Scopes
Yizhen Zheng, Yu Zheng, Xiaofei Zhou, et al.
2021 IEEE International Conference on Data Mining (ICDM) (2022), pp. 793-802
Open Access | Times Cited: 5
Yizhen Zheng, Yu Zheng, Xiaofei Zhou, et al.
2021 IEEE International Conference on Data Mining (ICDM) (2022), pp. 793-802
Open Access | Times Cited: 5
SAM: Query-efficient Adversarial Attacks against Graph Neural Networks
Chenhan Zhang, Shiyao Zhang, James J. Q. Yu, et al.
ACM Transactions on Privacy and Security (2023) Vol. 26, Iss. 4, pp. 1-19
Closed Access | Times Cited: 2
Chenhan Zhang, Shiyao Zhang, James J. Q. Yu, et al.
ACM Transactions on Privacy and Security (2023) Vol. 26, Iss. 4, pp. 1-19
Closed Access | Times Cited: 2
Drop edges and adapt: A fairness enforcing fine-tuning for graph neural networks
Indro Spinelli, Riccardo Bianchini, Simone Scardapane
Neural Networks (2023) Vol. 167, pp. 159-167
Open Access | Times Cited: 2
Indro Spinelli, Riccardo Bianchini, Simone Scardapane
Neural Networks (2023) Vol. 167, pp. 159-167
Open Access | Times Cited: 2
