Yudong Chen
Impact in
- Computational Mathematics top 0.1%
- Tensor decomposition and applications
- Computational Mechanics top 0.5%
- Sparse and Compressive Sensing Techniques
Papers in
-
- Statistical Methods and Inference 7
- Co-authors
- Jiashi FengShuicheng YanZhouchen LinCanyi LuWei LiuJiaming XuWenwu ZhuXin Wang
- Journals
- IEEE Transactions on Information Theory (10 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (4 papers)Forests (3 papers)ACM SIGMETRICS Performance Evaluation Review (3 papers)Ecological Indicators (2 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Yudong Chen
136 papers receiving 4.4k citations
Hit Papers
Peers
Comparison fields: 5 of 181
- Computational Mathematics 605
- Computational Mechanics 1.1k
- Computer Vision and Pattern Recognition 1.0k
- Signal Processing 409
- Artificial Intelligence 1.2k
Countries citing papers authored by Yudong Chen
This map shows the geographic impact of Yudong Chen'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 Yudong Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yudong Chen more than expected).
Fields of papers citing papers by Yudong Chen
This network shows the impact of papers produced by Yudong Chen. 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 Yudong Chen. The network helps show where Yudong Chen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yudong Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 8 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 3 | |
| 7 | 2023 | 4 | |
| 8 | 2023 | 4 | |
| 9 | 2023 | 25 | |
| 10 | 2022 | 13 | |
| 11 | 2021 | 53 | |
| 12 | 2021 | 5 | |
| 13 | 2021 | 2 | |
| 14 | Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression | 2019 | 2 |
| 15 | Fast Algorithms for Robust PCA via Gradient Descent | 2016 | 59 |
| 16 | 2014 | 5 | |
| 17 | Weighted Graph Clustering with Non-Uniform Uncertainties | 2014 | 5 |
| 18 | Clustering Sparse Graphs | 2012 | 33 |
| 19 | Principal Component Analysis of Fractional Brownian Motion | 2008 | 7 |
| 20 | Construction of a Subtractive cDNA Library from the Paralichthys olivaceus Embryonic Cells Induced by a Double-Stranded RNA Virus | 2005 | 7 |
About Yudong Chen
Yudong Chen is a scholar working on Computational Mathematics, Statistics and Probability, Computational Mechanics, Signal Processing and Statistical and Nonlinear Physics, having authored 143 papers that have together received 4.5k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (25 papers), Complex Network Analysis Techniques (14 papers), Stochastic Gradient Optimization Techniques (11 papers), Blind Source Separation Techniques (10 papers), Soil Carbon and Nitrogen Dynamics (9 papers), Statistical Methods and Inference (7 papers), Machine Learning and Algorithms (7 papers) and Complex Systems and Time Series Analysis (6 papers). The work is most often cited by research in Computational Mathematics (605 citations), Computational Mechanics (1.1k citations), Computer Vision and Pattern Recognition (1.0k citations), Signal Processing (409 citations) and Artificial Intelligence (1.2k citations). Yudong Chen has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Jiashi Feng, Shuicheng Yan, Zhouchen Lin, Canyi Lu, Wei Liu, Jiaming Xu, Wenwu Zhu, Xin Wang, Lili Su and Sujay Sanghavi. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Transactions on Pattern Analysis and Machine Intelligence, Forests, ACM SIGMETRICS Performance Evaluation Review and Ecological Indicators.
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.