Yongjun Xu

6.1k total citations · 5 hit papers
141 papers, 2.5k citations indexed

About

Yongjun Xu is a scholar working on Computer Networks and Communications, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Yongjun Xu has authored 141 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Computer Networks and Communications, 45 papers in Artificial Intelligence and 37 papers in Electrical and Electronic Engineering. Recurrent topics in Yongjun Xu's work include Energy Efficient Wireless Sensor Networks (19 papers), Advanced Neural Network Applications (15 papers) and Domain Adaptation and Few-Shot Learning (14 papers). Yongjun Xu is often cited by papers focused on Energy Efficient Wireless Sensor Networks (19 papers), Advanced Neural Network Applications (15 papers) and Domain Adaptation and Few-Shot Learning (14 papers). Yongjun Xu collaborates with scholars based in China, United States and Singapore. Yongjun Xu's co-authors include Fei Wang, Zhulin An, Zezhi Shao, Liehuang Zhu, Fei Wang, Chuanguang Yang, Lin Wu, Zhao Zhang, Qi Wang and Wei Wei and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Chemical Engineering Journal.

In The Last Decade

Yongjun Xu

129 papers receiving 2.4k citations

Hit Papers

Decoupled dynamic spatial-temporal graph neural network f... 2022 2026 2023 2024 2022 2022 2022 2022 2024 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Decoupled dynamic spatial-temporal graph neural network for traffic forecasting
    2022 185 citations Zezhi Shao, Fei Wang et al. profile →
  2. Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting
    2022 155 citations Zezhi Shao, Zhao Zhang et al. profile →
  3. Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting
    2022 152 citations Fei Wang, Yongjun Xu et al. profile →
  4. Cross-Image Relational Knowledge Distillation for Semantic Segmentation
    2022 141 citations Chuanguang Yang, Zhulin An et al. profile →
  5. Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis
    2024 61 citations Zezhi Shao, Fei Wang et al. IEEE Transactions on Knowledge and Data Engineering profile →

Peers

Yongjun Xu
Qi Han United States
Liang Liu China
Jiangtian Nie Singapore
Giovanni Pau Italy
Kaigui Bian China
Wancai Zhang China
Ammar Hawbani China
Inam Ullah China
Qi Han United States
Yongjun Xu
Citations per year, relative to Yongjun Xu Yongjun Xu (= 1×) peers Qi Han

Countries citing papers authored by Yongjun Xu

Since Specialization
Citations

This map shows the geographic impact of Yongjun Xu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yongjun Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yongjun Xu more than expected).

Fields of papers citing papers by Yongjun Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yongjun Xu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yongjun Xu. The network helps show where Yongjun Xu may publish in the future.

Co-authorship network of co-authors of Yongjun Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Yongjun Xu. A scholar is included among the top collaborators of Yongjun Xu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yongjun Xu. Yongjun Xu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Liu, Ruiqi, et al.. (2025). Low-redundancy distillation for continual learning. Pattern Recognition. 167. 111712–111712. 1 indexed citations
2.
Yu, Xiaowei, et al.. (2025). AF-YOLO: Asymptotic Feature Extraction and Fusion for Aerial Object Detection. IEEE Transactions on Circuits and Systems for Video Technology. 36(1). 63–78.
3.
Yu, Chengqing, Fei Wang, Zezhi Shao, et al.. (2025). GinAR+: A Robust End-to-End Framework for Multivariate Time Series Forecasting With Missing Values. IEEE Transactions on Knowledge and Data Engineering. 37(8). 4635–4648. 5 indexed citations
4.
5.
Gu, Haoyu, Yang Zhang, Zhongjun Cheng, et al.. (2024). Smart reconfigurable electromagnetic metamaterials based on thermadapt shape memory Poly(ethylene–vinyl acetate). Chemical Engineering Journal. 491. 152106–152106. 2 indexed citations
6.
Li, Yujie, et al.. (2024). Trajectory-User Linking via Multi-Scale Graph Attention Network. Pattern Recognition. 158. 110978–110978. 2 indexed citations
7.
Yu, Chengqing, Fei Wang, Yilun Wang, et al.. (2024). MGSFformer: A Multi-Granularity Spatiotemporal Fusion Transformer for air quality prediction. Information Fusion. 113. 102607–102607. 26 indexed citations
8.
Li, Dan, et al.. (2024). Deep Distributional Reinforcement Learning-Based Adaptive Routing With Guaranteed Delay Bounds. IEEE/ACM Transactions on Networking. 32(6). 4692–4706. 2 indexed citations
9.
Feng, Wei, Chuanguang Yang, Zhulin An, et al.. (2024). Relational Diffusion Distillation for Efficient Image Generation. 205–213. 5 indexed citations
10.
Shao, Zezhi, Fei Wang, Yongjun Xu, et al.. (2024). Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis. IEEE Transactions on Knowledge and Data Engineering. 37(1). 291–305. 61 indexed citations breakdown →
11.
Yu, Chengqing, Fei Wang, Zezhi Shao, et al.. (2024). GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing. 3989–4000. 19 indexed citations
12.
Li, Sen, et al.. (2024). Approximate data mapping in refresh-free DRAM for energy-efficient computing in modern mobile systems. Computer Communications. 216. 151–158. 1 indexed citations
13.
Xie, Ruobing, Zhao Zhang, Xu Zhang, et al.. (2024). DFGNN: Dual-frequency Graph Neural Network for Sign-aware Feedback. 3437–3447. 4 indexed citations
14.
An, Zhulin, et al.. (2023). Sketch-fusion: A gradient compression method with multi-layer fusion for communication-efficient distributed training. Journal of Parallel and Distributed Computing. 185. 104811–104811. 5 indexed citations
15.
Zhang, Zhao, Fuwei Zhang, Fuzhen Zhuang, & Yongjun Xu. (2023). Knowledge Graph Error Detection with Hierarchical Path Structure. 4430–4434. 3 indexed citations
16.
Zhang, Yuting, et al.. (2023). Modeling Dual Period-Varying Preferences for Takeaway Recommendation. arXiv (Cornell University). 5628–5638. 3 indexed citations
17.
Xie, Ruobing, Zhao Zhang, Yongchun Zhu, et al.. (2023). Attacking Pre-trained Recommendation. 1811–1815. 3 indexed citations
18.
Li, Qiming, et al.. (2023). Topic-aware Intention Network for Explainable Recommendation with Knowledge Enhancement. ACM Transactions on Information Systems. 41(4). 1–23. 6 indexed citations
19.
20.
Shao, Zezhi, Yongjun Xu, Wei Wei, et al.. (2022). Heterogeneous Graph Neural Network With Multi-View Representation Learning. IEEE Transactions on Knowledge and Data Engineering. 35(11). 11476–11488. 22 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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