Wenxuan Tu
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 1%
- Statistical and Nonlinear Physics top 2%
- Information Systems top 5%
- Media Technology top 2%
- Co-authors
- Xinwang LiuSihang ZhouEn ZhuYue LiuSiwei WangKe LiangXihong YangJieren Cheng
- Topics
- Advanced Graph Neural Networks (23 papers)Complex Network Analysis Techniques (11 papers)Recommender Systems and Techniques (8 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Geoscience and Remote SensingIEEE Transactions on Image Processing
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Wenxuan Tu
45 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 86
- Artificial Intelligence 1.2k
- Computer Vision and Pattern Recognition 794
- Statistical and Nonlinear Physics 319
- Information Systems 216
- Media Technology 151
Countries citing papers authored by Wenxuan Tu
This map shows the geographic impact of Wenxuan Tu'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 Wenxuan Tu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wenxuan Tu more than expected).
Fields of papers citing papers by Wenxuan Tu
This network shows the impact of papers produced by Wenxuan Tu. 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 Wenxuan Tu. The network helps show where Wenxuan Tu may publish in the future.
Co-authorship network of co-authors of Wenxuan Tu
This figure shows the co-authorship network connecting the top 25 collaborators of Wenxuan Tu. A scholar is included among the top collaborators of Wenxuan Tu 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 Wenxuan Tu. Wenxuan Tu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 18 | |
| 5 | 25 | |
| 6 | 5 | |
| 7 | 5 | |
| 8 | A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multi-Modalbreakdown → | 76 |
| 9 | 11 | |
| 10 | 5 | |
| 11 | Contrastive Multiview Subspace Clustering of Hyperspectral Images Based on Graph Convolutional Networksbreakdown → | 73 |
| 12 | 4 | |
| 13 | 69 | |
| 14 | 64 | |
| 15 | 50 | |
| 16 | 18 | |
| 17 | Simple Contrastive Graph Clusteringbreakdown → | 99 |
| 18 | 19 | |
| 19 | 68 | |
| 20 | One Pass Late Fusion Multi-view Clustering | 11 |
About Wenxuan Tu
Wenxuan Tu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 50 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (23 papers), Complex Network Analysis Techniques (11 papers) and Recommender Systems and Techniques (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (794 citations), Artificial Intelligence (1.2k citations) and Computational Mathematics (21 citations). Wenxuan Tu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Xinwang Liu, Sihang Zhou, En Zhu, Yue Liu, Siwei Wang, Ke Liang, Xihong Yang, Jieren Cheng, Zhiping Cai and Meng Liu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.
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.