Junming Yin
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Topic Modeling
Papers in
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- Advanced Graph Neural Networks 3
- Sentiment Analysis and Opinion Mining 2
- Advanced Text Analysis Techniques 2
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- Bioinformatics and Genomic Networks 4
- Co-authors
- Linhong Zhu (2 shared papers)Aram Galstyan (2 shared papers)Greg Ver Steeg (2 shared papers)Dong Guo (2 shared papers)Eric P. Xing (6 shared papers)Weifeng Li (3 shared papers)Yun S. Song (1 shared paper)Michael I. Jordan (2 shared papers)
- Journals
- Bioinformatics (2 papers)IEEE Transactions on Knowledge and Data Engineering (2 papers)Pacific-Basin Finance Journal (1 paper)Journal of Machine Learning Research (1 paper)PLoS ONE (1 paper)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Junming Yin
22 papers receiving 320 citations
Peers
Comparison fields: 5 of 61
- Statistical and Nonlinear Physics 163
- Artificial Intelligence 210
- Computational Mathematics 3
- Transportation 17
- Information Systems 46
Countries citing papers authored by Junming Yin
This map shows the geographic impact of Junming Yin'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 Junming Yin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junming Yin more than expected).
Fields of papers citing papers by Junming Yin
This network shows the impact of papers produced by Junming Yin. 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 Junming Yin. The network helps show where Junming Yin may publish in the future.
Co-authors
The 25 scholars most cited alongside Junming Yin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 183 | |
| 2 | 2017 | 21 | |
| 3 | 2009 | 20 | |
| 4 | 2021 | 17 | |
| 5 | 2016 | 13 | |
| 6 | 2018 | 8 | |
| 7 | 2016 | 8 | |
| 8 | 2011 | 8 | |
| 9 | 2017 | 7 | |
| 10 | 2006 | 6 | |
| 11 | 2018 | 6 | |
| 12 | 2022 | 5 | |
| 13 | 2014 | 5 | |
| 14 | Identifying high quality carding services in underground economy using nonparametric supervised topic model | 2016 | 4 |
| 15 | 2016 | 4 | |
| 16 | 2022 | 4 | |
| 17 | 2022 | 3 | |
| 18 | Relaxed Multivariate Bernoulli Distribution and Its Applications to Deep Generative Models | 2020 | 2 |
| 19 | 2024 | 2 | |
| 20 | 2018 | 2 |
About Junming Yin
Junming Yin is a scholar working on Artificial Intelligence, Molecular Biology, Statistical and Nonlinear Physics, Genetics and Economics and Econometrics, having authored 23 papers that have together received 330 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (5 papers), Bioinformatics and Genomic Networks (4 papers), Advanced Graph Neural Networks (3 papers), Genetic Associations and Epidemiology (3 papers), Auction Theory and Applications (2 papers), Spam and Phishing Detection (2 papers), Sentiment Analysis and Opinion Mining (2 papers) and Advanced Text Analysis Techniques (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (163 citations), Artificial Intelligence (210 citations), Computational Mathematics (3 citations), Transportation (17 citations) and Information Systems (46 citations). Junming Yin has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Linhong Zhu, Aram Galstyan, Greg Ver Steeg, Dong Guo, Eric P. Xing, Weifeng Li, Yun S. Song, Michael I. Jordan, Qirong Ho and Hsinchun Chen. Their work appears in journals such as Bioinformatics, IEEE Transactions on Knowledge and Data Engineering, Pacific-Basin Finance Journal, Journal of Machine Learning Research and PLoS ONE.
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.