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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:

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: 72

Showing 1-25 of 72 citing articles:

Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey
Guangyin Jin, Yuxuan Liang, Yuchen Fang, et al.
IEEE Transactions on Knowledge and Data Engineering (2023) Vol. 36, Iss. 10, pp. 5388-5408
Open Access | Times Cited: 134
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection
Ming Jin, Huan Yee Koh, Qingsong Wen, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2024) Vol. 46, Iss. 12, pp. 10466-10485
Open Access | Times Cited: 79
Deep Learning for Time Series Forecasting: Advances and Open Problems
Angelo Casolaro, Vincenzo Capone, Gennaro Iannuzzo, et al.
Information (2023) Vol. 14, Iss. 11, pp. 598-598
Open Access | Times Cited: 44
Learning Graph ODE for Continuous-Time Sequential Recommendation
Yifang Qin, Wei Ju, Hongjun Wu, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 7, pp. 3224-3236
Open Access | Times Cited: 23
Deep learning for time series forecasting: a survey
Xiangjie Kong, Zhenghao Chen, Weiyao Liu, et al.
International Journal of Machine Learning and Cybernetics (2025)
Open Access | Times Cited: 2
GGNet: A novel graph structure for power forecasting in renewable power plants considering temporal lead-lag correlations
Nanyang Zhu, Ying Wang, Kun Yuan, et al.
Applied Energy (2024) Vol. 364, pp. 123194-123194
Closed Access | Times Cited: 13
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: 10
High–low frequency dynamic interactive fusion network for multivariate time series forecasting
Chengci Wang, Zhuolin Li, Jie Yu, et al.
Knowledge-Based Systems (2025) Vol. 310, pp. 112951-112951
Closed Access | Times Cited: 1
DGMSCL: A dynamic graph mixed supervised contrastive learning approach for class imbalanced multivariate time series classification
Lipeng Qian, Qiong Zuo, Dahu Li, et al.
Neural Networks (2025) Vol. 185, pp. 107131-107131
Closed Access | Times Cited: 1
Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion
Linhao Luo, Yuan-Fang Li, Gholamreza Haffari, et al.
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2023), pp. 900-910
Open Access | Times Cited: 18
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: 18
Time series forecasting of wheat crop productivity in Egypt using deep learning techniques
Amal Mahmoud, Ammar Mohammed, Magdy Abdel Wahab, et al.
International Journal of Data Science and Analytics (2024)
Closed Access | Times Cited: 7
AutoCTS++: zero-shot joint neural architecture and hyperparameter search for correlated time series forecasting
Xinle Wu, Xingjian Wu, Bin Yang, et al.
The VLDB Journal (2024) Vol. 33, Iss. 5, pp. 1743-1770
Closed Access | Times Cited: 6
Adaptive Decision Spatio-temporal neural ODE for traffic flow forecasting with Multi-Kernel Temporal Dynamic Dilation Convolution
Zihao Chu, Wenming Ma, Mingqi Li, et al.
Neural Networks (2024) Vol. 179, pp. 106549-106549
Closed Access | Times Cited: 5
Learning Continuous Spatial-Temporal Evolution via Dynamic Graph Neural Differential Equations for Traffic Flow Forecasting
Hongli Shi, Wensheng Zhang
Information Sciences (2025), pp. 121845-121845
Closed Access
A traffic prediction method for missing data scenarios: graph convolutional recurrent ordinary differential equation network
Ming Jiang, Zhiwei Liu, Yan Xu
Complex & Intelligent Systems (2025) Vol. 11, Iss. 2
Open Access
Dynamic Spatio-Temporal Residual Hypergraph Convolutional Networks for Traffic Flow Forecasting
Jun Su, Hairu Wang, Кrzysztof Przystupa, et al.
Transportation Research Record Journal of the Transportation Research Board (2025)
Closed Access
Knowledge fusion and spatio-temporal modeling for dynamic bottleneck prediction in sustainable production processes
Tao Wu, Jie Li, Jinsong Bao, et al.
International Journal of Computer Integrated Manufacturing (2025), pp. 1-17
Closed Access
Dynamic Graph-Based Bilateral Recurrent Imputation Network for Multivariate Time Series
Xiaochen Lai, Zheng Zhang, Liyong Zhang, et al.
Neural Networks (2025) Vol. 186, pp. 107298-107298
Closed Access
Design of a low-power intelligent system for optimizing railway tunnel settlement data stream processing using TinyMLt
Bingfeng Lv, Lei Wang, Xingyue Liu, et al.
Computers & Electrical Engineering (2025) Vol. 123, pp. 110197-110197
Closed Access
Attention based spatial-temporal multi-graph ordinary differential equation network for traffic flow prediction
Y.Z. Chen, Cheng Li, Shuang Li
Engineering Applications of Artificial Intelligence (2025) Vol. 149, pp. 110526-110526
Closed Access
Representation Learning Based on Ordinary Differential Equations for Dynamic Networks
Dongjie Li, Dong Li, Guang Lian
ACM Transactions on Knowledge Discovery from Data (2025)
Closed Access
A novel anomaly detection method for multivariate time series based on spatial-temporal graph learning
Jing Zhang, Xin Wang, Yang Yang, et al.
Journal of King Saud University - Computer and Information Sciences (2025) Vol. 37, Iss. 1-2
Open Access
Future Matters for Present: Towards Effective Physical Simulation over Meshes
Xiao Luo, Junyu Luo, HuiYu Jiang, et al.
(2025), pp. 906-917
Closed Access
Bi-Dynamic Graph ODE for Opinion Evolution
Bowen Duan, Henggang Deng, Jinghua Piao, et al.
(2025), pp. 260-270
Closed Access
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