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:
Learning causality with graphs
Jing Ma, Jundong Li
AI Magazine (2022) Vol. 43, Iss. 4, pp. 365-375
Open Access | Times Cited: 10
Jing Ma, Jundong Li
AI Magazine (2022) Vol. 43, Iss. 4, pp. 365-375
Open Access | Times Cited: 10
Showing 10 citing articles:
A Comprehensive Survey on Deep Graph Representation Learning
Wei Ju, Zheng Fang, Yiyang Gu, et al.
Neural Networks (2024) Vol. 173, pp. 106207-106207
Open Access | Times Cited: 124
Wei Ju, Zheng Fang, Yiyang Gu, et al.
Neural Networks (2024) Vol. 173, pp. 106207-106207
Open Access | Times Cited: 124
Invariant Graph Learning for Causal Effect Estimation
Yongduo Sui, Caizhi Tang, Zhixuan Chu, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 2552-2562
Closed Access | Times Cited: 2
Yongduo Sui, Caizhi Tang, Zhixuan Chu, et al.
Proceedings of the ACM Web Conference 2022 (2024), pp. 2552-2562
Closed Access | Times Cited: 2
Causal Inference with Latent Variables: Recent Advances and Future Prospectives
Yaochen Zhu, Yinhan He, Jing Ma, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 6677-6687
Open Access | Times Cited: 2
Yaochen Zhu, Yinhan He, Jing Ma, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2024), pp. 6677-6687
Open Access | Times Cited: 2
When Causal Inference Meets Graph Machine Learning
Jing Ma
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 20, pp. 22676-22676
Open Access | Times Cited: 1
Jing Ma
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 20, pp. 22676-22676
Open Access | Times Cited: 1
A Comprehensive Survey on Deep Graph Representation Learning
Wei Ju, Zheng Fang, Yiyang Gu, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 3
Wei Ju, Zheng Fang, Yiyang Gu, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 3
Causal Effect Estimation on Hierarchical Spatial Graph Data
Koh Takeuchi, Ryo Nishida, Hisashi Kashima, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2023), pp. 2145-2154
Open Access | Times Cited: 2
Koh Takeuchi, Ryo Nishida, Hisashi Kashima, et al.
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2023), pp. 2145-2154
Open Access | Times Cited: 2
TrustLOG: The Second Workshop on Trustworthy Learning on Graphs
Jingrui He, Jian Kang, Fatemeh Nargesian, et al.
(2024), pp. 1785-1788
Open Access
Jingrui He, Jian Kang, Fatemeh Nargesian, et al.
(2024), pp. 1785-1788
Open Access
A survey of out‐of‐distribution generalization for graph machine learning from a causal view
Jing Ma
AI Magazine (2024)
Open Access
Jing Ma
AI Magazine (2024)
Open Access
State-Of-The-Art and Challenges in Causal Inference on Graphs: Confounders and Interferences
J. H. Chou, Jiangzhuo Chen, Madhav Marathe
(2024), pp. 1-13
Closed Access
J. H. Chou, Jiangzhuo Chen, Madhav Marathe
(2024), pp. 1-13
Closed Access
Enhancing targeted tumor treatment: A novel fuzzy logic framework for precision drug delivery strategy selection
Ruizi Zhang, Yue Sun, Yifan Chen
Computers in Biology and Medicine (2024) Vol. 180, pp. 109008-109008
Closed Access
Ruizi Zhang, Yue Sun, Yifan Chen
Computers in Biology and Medicine (2024) Vol. 180, pp. 109008-109008
Closed Access
