Chun-Ta Lu
Impact in
- Computational Mathematics top 2%
-
- FinTech, Crowdfunding, Digital Finance
Papers in
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- Advanced Graph Neural Networks 14
- Topic Modeling 6
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- Tensor decomposition and applications 8
- Co-authors
- Philip S. Yu (30 shared papers)Lifang He (15 shared papers)Weixiang Shao (6 shared papers)Sihong Xie (6 shared papers)Xiangnan Kong (1 shared paper)Ann Barnett Ragin (7 shared papers)Bokai Cao (7 shared papers)Guixiang Ma (4 shared papers)
- Journals
- Knowledge and Information Systems (1 paper)Lecture notes in computer science (3 papers)International Joint Conference on Artificial Intelligence (1 paper)UvA-DARE (University of Amsterdam) (1 paper)arXiv (Cornell University) (2 papers)
- Partner nations
- United StatesChinaSwitzerland
In The Last Decade
Chun-Ta Lu
40 papers receiving 925 citations
Peers
Comparison fields: 5 of 78
- Computational Mathematics 68
- Management Information Systems 143
- Artificial Intelligence 438
- Statistical and Nonlinear Physics 145
- Computer Vision and Pattern Recognition 237
Countries citing papers authored by Chun-Ta Lu
This map shows the geographic impact of Chun-Ta Lu'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 Chun-Ta Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chun-Ta Lu more than expected).
Fields of papers citing papers by Chun-Ta Lu
This network shows the impact of papers produced by Chun-Ta Lu. 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 Chun-Ta Lu. The network helps show where Chun-Ta Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Chun-Ta Lu, 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 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 159 | |
| 2 | 2016 | 92 | |
| 3 | 2016 | 60 | |
| 4 | 2016 | 58 | |
| 5 | 2017 | 46 | |
| 6 | 2017 | 43 | |
| 7 | 2017 | 40 | |
| 8 | 2014 | 31 | |
| 9 | 2017 | 28 | |
| 10 | 2017 | 24 | |
| 11 | 2019 | 22 | |
| 12 | 2017 | 21 | |
| 13 | 2024 | 20 | |
| 14 | 2019 | 19 | |
| 15 | 2016 | 18 | |
| 16 | 2016 | 18 | |
| 17 | 2011 | 17 | |
| 18 | 2019 | 16 | |
| 19 | 2020 | 16 | |
| 20 | 2019 | 15 |
About Chun-Ta Lu
Chun-Ta Lu is a scholar working on Artificial Intelligence, Computational Mathematics, Information Systems, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 41 papers that have together received 942 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (14 papers), Recommender Systems and Techniques (10 papers), Tensor decomposition and applications (8 papers), Functional Brain Connectivity Studies (7 papers), Complex Network Analysis Techniques (6 papers), Topic Modeling (6 papers), Multimodal Machine Learning Applications (5 papers) and Advanced Neuroimaging Techniques and Applications (5 papers). The work is most often cited by research in Computational Mathematics (68 citations), Management Information Systems (143 citations), Artificial Intelligence (438 citations), Statistical and Nonlinear Physics (145 citations) and Computer Vision and Pattern Recognition (237 citations). Chun-Ta Lu has collaborated with scholars based in United States, China and Switzerland. Frequent co-authors include Philip S. Yu, Lifang He, Weixiang Shao, Sihong Xie, Xiangnan Kong, Ann Barnett Ragin, Bokai Cao, Guixiang Ma, Xiaokai Wei and Linlin Shen. Their work appears in journals such as Knowledge and Information Systems, Lecture notes in computer science, International Joint Conference on Artificial Intelligence, UvA-DARE (University of Amsterdam) and arXiv (Cornell University).
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.