Cheng Yang
- Artificial Intelligence top 0.2%
- Information Systems top 0.5%
- Statistical and Nonlinear Physics top 0.5%
- Computer Vision and Pattern Recognition top 1%
- Computer Networks and Communications top 2%
- Co-authors
- Maosong SunZhiyuan LiuGanqu CuiZhengyan ZhangShengding HuChangcheng LiJie ZhouLifeng Wang
- Topics
- Advanced Graph Neural Networks (40 papers)Topic Modeling (31 papers)Complex Network Analysis Techniques (20 papers)
- Journals
- Angewandte Chemie International EditionSHILAP Revista de lepidopterologíaNano Letters
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Cheng Yang
125 papers receiving 6.3k citations
Hit Papers
Peers
Comparison fields: 5 of 193
- Artificial Intelligence 3.5k
- Information Systems 1.2k
- Statistical and Nonlinear Physics 1.2k
- Computer Vision and Pattern Recognition 1.0k
- Computer Networks and Communications 681
Countries citing papers authored by Cheng Yang
This map shows the geographic impact of Cheng Yang'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 Cheng Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cheng Yang more than expected).
Fields of papers citing papers by Cheng Yang
This network shows the impact of papers produced by Cheng Yang. 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 Cheng Yang. The network helps show where Cheng Yang may publish in the future.
Co-authorship network of co-authors of Cheng Yang
This figure shows the co-authorship network connecting the top 25 collaborators of Cheng Yang. A scholar is included among the top collaborators of Cheng Yang 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 Cheng Yang. Cheng Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 8 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 4 | |
| 11 | 3 | |
| 12 | 6 | |
| 13 | 2 | |
| 14 | 7 | |
| 15 | 2 | |
| 16 | 43 | |
| 17 | 12 | |
| 18 | 82 | |
| 19 | 30 | |
| 20 | BML: A High-performance, Low-cost Gradient Synchronization Algorithm for DML Training | 17 |
About Cheng Yang
Cheng Yang is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Information Systems, having authored 148 papers that have together received 6.5k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (40 papers), Topic Modeling (31 papers) and Complex Network Analysis Techniques (20 papers). The work is most often cited by research in Artificial Intelligence (3.5k citations), Statistical and Nonlinear Physics (1.2k citations) and Information Systems (1.2k citations). Cheng Yang has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Maosong Sun, Zhiyuan Liu, Ganqu Cui, Zhengyan Zhang, Shengding Hu, Changcheng Li, Jie Zhou, Lifeng Wang, Chuan Shi and Edward Yi Chang. Their work appears in journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and Nano Letters.
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.