Chen Xu
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Media Technology top 5%
- Computational Mechanics top 10%
- Topics
- Sparse and Compressive Sensing Techniques (12 papers)Face and Expression Recognition (12 papers)Machine Learning and ELM (7 papers)
- Journals
- Journal of the American Statistical AssociationIEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Geoscience and Remote Sensing
- Partner nations
- ChinaCanadaUnited States
In The Last Decade
Chen Xu
55 papers receiving 921 citations
Peers
Comparison fields: 5 of 106
- Artificial Intelligence 331
- Computer Vision and Pattern Recognition 287
- Information Systems 167
- Media Technology 116
- Computational Mechanics 91
Countries citing papers authored by Chen Xu
This map shows the geographic impact of Chen 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 Chen Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chen Xu more than expected).
Fields of papers citing papers by Chen Xu
This network shows the impact of papers produced by Chen 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 Chen Xu. The network helps show where Chen Xu may publish in the future.
Co-authorship network of co-authors of Chen Xu
This figure shows the co-authorship network connecting the top 25 collaborators of Chen Xu. A scholar is included among the top collaborators of Chen 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 Chen Xu. Chen Xu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 4 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 5 | |
| 9 | 6 | |
| 10 | 65 | |
| 11 | 52 | |
| 12 | Distributed feature screening via componentwise debiasing | 1 |
| 13 | Multi-task Additive Models for Robust Estimation and Automatic Structure Discovery | 6 |
| 14 | 24 | |
| 15 | Alternating Multi-bit Quantization for Recurrent Neural Networks | 28 |
| 16 | 74 | |
| 17 | 2 | |
| 18 | 38 | |
| 19 | Model for prediction of saltwater intrusion based on partial mutual information and fixed size least squares support vector machine | 1 |
| 20 | Application Research on Complex Network of Industrial Ecological System | 1 |
About Chen Xu
Chen Xu is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 59 papers that have together received 950 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (12 papers), Face and Expression Recognition (12 papers) and Machine Learning and ELM (7 papers). The work is most often cited by research in Computational Mathematics (38 citations), Computer Vision and Pattern Recognition (287 citations) and Media Technology (116 citations). Chen Xu has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Xiangyong Cao, Xueyang Fu, Deyu Meng, Bin Zou, Yuan Yan Tang, Jacek M. Żurada, Jiahua Chen, Jian Wang, Jie Xu and Wenwen Ye. Their work appears in journals such as Journal of the American Statistical Association, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Geoscience and Remote Sensing.
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.