Xiaojing Ye

2.0k total citations · 1 hit paper
54 papers, 979 citations indexed

About

Xiaojing Ye is a scholar working on Radiology, Nuclear Medicine and Imaging, Computational Mechanics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Xiaojing Ye has authored 54 papers receiving a total of 979 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Radiology, Nuclear Medicine and Imaging, 18 papers in Computational Mechanics and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in Xiaojing Ye's work include Medical Imaging Techniques and Applications (17 papers), Sparse and Compressive Sensing Techniques (14 papers) and Advanced MRI Techniques and Applications (11 papers). Xiaojing Ye is often cited by papers focused on Medical Imaging Techniques and Applications (17 papers), Sparse and Compressive Sensing Techniques (14 papers) and Advanced MRI Techniques and Applications (11 papers). Xiaojing Ye collaborates with scholars based in United States, China and Finland. Xiaojing Ye's co-authors include Yunmei Chen, Haomin Zhou, Yaohua Zang, Gang Bao, Feng Huang, Junwei Huang, Feng Huang, William W. Hager, Liang Zhao and Wen‐Zhan Song and has published in prestigious journals such as Journal of Computational Physics, IEEE Transactions on Image Processing and Magnetic Resonance in Medicine.

In The Last Decade

Xiaojing Ye

47 papers receiving 937 citations

Hit Papers

Weak adversarial networks for high-dimensional partial di... 2020 2026 2022 2024 2020 50 100 150 200
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. Weak adversarial networks for high-dimensional partial differential equations
    2020 228 citations Xiaojing Ye, Haomin Zhou et al. Journal of Computational Physics profile →

Peers

Xiaojing Ye
Rachel Ward United States
Gregery T. Buzzard United States
Ben Adcock Canada
Zheng‐Hai Huang China
Anders C. Hansen United Kingdom
Gaohang Yu China
Qiyu Sun United States
C. Si̇nan Güntürk United States
Simon Setzer Germany
Xiaobai Sun United States
Rachel Ward United States
Xiaojing Ye
Citations per year, relative to Xiaojing Ye Xiaojing Ye (= 1×) peers Rachel Ward

Countries citing papers authored by Xiaojing Ye

Since Specialization
Citations

This map shows the geographic impact of Xiaojing Ye'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 Xiaojing Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaojing Ye more than expected).

Fields of papers citing papers by Xiaojing Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaojing Ye. 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 Xiaojing Ye. The network helps show where Xiaojing Ye may publish in the future.

Co-authorship network of co-authors of Xiaojing Ye

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaojing Ye. A scholar is included among the top collaborators of Xiaojing Ye 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 Xiaojing Ye. Xiaojing Ye 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.
Smirnova, Alexandra & Xiaojing Ye. (2024). On optimal control at the onset of a new viral outbreak. Infectious Disease Modelling. 9(4). 995–1006. 2 indexed citations
2.
Smirnova, Alexandra, et al.. (2024). Optimal Epidemic Control with Nonmedical and Medical Interventions. Mathematics. 12(18). 2811–2811.
3.
Ye, Xiaojing, et al.. (2024). Neural Control of Parametric Solutions for High-Dimensional Evolution PDEs. SIAM Journal on Scientific Computing. 46(2). C155–C185. 4 indexed citations
4.
Zhang, Qingchao, et al.. (2024). Provably Convergent Learned Inexact Descent Algorithm for Low-Dose CT Reconstruction. Journal of Scientific Computing. 101(1). 1 indexed citations
5.
Liu, Shu, et al.. (2024). Parameterized Wasserstein gradient flow. Journal of Computational Physics. 524. 113660–113660.
6.
Wu, Jing, et al.. (2023). Image dehazing based on polarization optimization and atmosphere light correction. Optics and Precision Engineering. 31(12). 1827–1840. 3 indexed citations
7.
Zhang, Qingchao, Xiaojing Ye, & Yunmei Chen. (2022). Extra Proximal-Gradient Network with Learned Regularization for Image Compressive Sensing Reconstruction. Journal of Imaging. 8(7). 178–178. 5 indexed citations
8.
Chen, Yunmei, et al.. (2022). An optimal control framework for joint-channel parallel MRI reconstruction without coil sensitivities. Magnetic Resonance Imaging. 89. 1–11. 7 indexed citations
9.
Chow, Shui-Nee, Xiaojing Ye, Hongyuan Zha, & Haomin Zhou. (2018). Influence prediction for continuous-time information propagation on networks. Networks and Heterogeneous Media. 13(4). 567–583. 1 indexed citations
10.
Wang, Yichen, Xiaojing Ye, Haomin Zhou, Hongyuan Zha, & Le Song. (2017). Linking Micro Event History to Macro Prediction in Point Process Models. International Conference on Artificial Intelligence and Statistics. 1375–1384. 9 indexed citations
11.
Farajtabar, Mehrdad, Jiachen Yang, Xiaojing Ye, et al.. (2017). Fake News Mitigation via Point Process Based Intervention. International Conference on Machine Learning. 1097–1106. 15 indexed citations
12.
Yang, Jiachen, Xiaojing Ye, Rakshit Trivedi, Huan Xu, & Hongyuan Zha. (2017). Deep Mean Field Games for Learning Optimal Behavior Policy of Large Populations.. arXiv (Cornell University). 9 indexed citations
13.
Wang, Yichen, Xiaojing Ye, Hongyuan Zha, & Le Song. (2017). Predicting User Activity Level In Point Processes With Mass Transport Equation. Neural Information Processing Systems. 30. 1645–1655. 5 indexed citations
14.
Xiao, Shuai, Mehrdad Farajtabar, Xiaojing Ye, et al.. (2017). Wasserstein Learning of Deep Generative Point Process Models. Neural Information Processing Systems. 30. 3247–3257. 16 indexed citations
15.
Farajtabar, Mehrdad, Xiaojing Ye, Sahar Harati, Le Song, & Hongyuan Zha. (2016). Multistage Campaigning in Social Networks. arXiv (Cornell University). 29. 4718–4726. 6 indexed citations
16.
Niu, Tianye, et al.. (2014). Accelerated barrier optimization compressed sensing (ABOCS) for CT reconstruction with improved convergence. Physics in Medicine and Biology. 59(7). 1801–1814. 27 indexed citations
17.
Liu, Meizhu, Le Lü, Xiaojing Ye, Shipeng Yu, & Marcos Salganicoff. (2011). Sparse Classification for Computer Aided Diagnosis Using Learned Dictionaries. Lecture notes in computer science. 14(Pt 3). 41–48. 31 indexed citations
18.
Ye, Xiaojing, Yunmei Chen, & Feng Huang. (2010). Computational Acceleration for MR Image Reconstruction in Partially Parallel Imaging. IEEE Transactions on Medical Imaging. 30(5). 1055–1063. 58 indexed citations
19.
Huang, Feng, Yunmei Chen, Wotao Yin, et al.. (2010). A rapid and robust numerical algorithm for sensitivity encoding with sparsity constraints: Self‐feeding sparse SENSE. Magnetic Resonance in Medicine. 64(4). 1078–1088. 42 indexed citations
20.
Ye, Xiaojing, Yunmei Chen, & Feng Huang. (2009). MR Image Reconstruction via Sparse Representation: Modeling and Algorithm.. IPCV. 10–16. 2 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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