Wei Ju
Impact in
- Artificial Intelligence top 2%
- Advanced Graph Neural Networks
- Domain Adaptation and Few-Shot Learning
- Topic Modeling
- Text and Document Classification Technologies
- Transportation top 5%
Papers in
-
- Advanced Graph Neural Networks 30
- Domain Adaptation and Few-Shot Learning 13
- Topic Modeling 8
- Text and Document Classification Technologies 6
- Machine Learning and Algorithms 5
- Natural Language Processing Techniques 3
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- Recommender Systems and Techniques 10
- Co-authors
- Ming Zhang (36 shared papers)Xiao Luo (31 shared papers)Yifang Qin (18 shared papers)Yiyang Gu (12 shared papers)Xian‐Sheng Hua (11 shared papers)Chong Chen (11 shared papers)Yifan Wang (11 shared papers)Minghua Deng (4 shared papers)
- Journals
- Neural Networks (4 papers)ACM Transactions on Knowledge Discovery from Data (3 papers)IEEE Transactions on Multimedia (3 papers)IEEE Transactions on Neural Networks and Learning Systems (3 papers)ACM Transactions on Information Systems (2 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Wei Ju
70 papers receiving 1.1k citations
Wei Ju's Hit Papers
Peers
Comparison fields: 5 of 102
- Artificial Intelligence 654
- Transportation 88
- Computer Vision and Pattern Recognition 227
- Statistical and Nonlinear Physics 123
- Information Systems 222
Countries citing papers authored by Wei Ju
This map shows the geographic impact of Wei Ju'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 Wei Ju with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Ju more than expected).
Fields of papers citing papers by Wei Ju
This network shows the impact of papers produced by Wei Ju. 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 Wei Ju. The network helps show where Wei Ju may publish in the future.
Co-authors
The 25 scholars most cited alongside Wei Ju, 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 78 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A Comprehensive Survey on Deep Graph Representation Learning Hit paper breakdown → | 2024 | 159 |
| 2 | 2022 | 55 | |
| 3 | 2023 | 50 | |
| 4 | 2023 | 47 | |
| 5 | 2023 | 47 | |
| 6 | 2022 | 45 | |
| 7 | 2023 | 43 | |
| 8 | 2023 | 40 | |
| 9 | 2024 | 37 | |
| 10 | 2022 | 37 | |
| 11 | 2015 | 34 | |
| 12 | 2024 | 34 | |
| 13 | 2022 | 34 | |
| 14 | 2023 | 33 | |
| 15 | 2022 | 33 | |
| 16 | 2024 | 32 | |
| 17 | 2022 | 29 | |
| 18 | 2023 | 25 | |
| 19 | 2022 | 24 | |
| 20 | 2022 | 23 |
About Wei Ju
Wei Ju is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Transportation, having authored 78 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (30 papers), Domain Adaptation and Few-Shot Learning (13 papers), Recommender Systems and Techniques (10 papers), Topic Modeling (8 papers), Complex Network Analysis Techniques (7 papers), Text and Document Classification Technologies (6 papers), Machine Learning and Algorithms (5 papers) and Natural Language Processing Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (654 citations), Transportation (88 citations), Computer Vision and Pattern Recognition (227 citations), Statistical and Nonlinear Physics (123 citations) and Information Systems (222 citations). Wei Ju has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Ming Zhang, Xiao Luo, Yifang Qin, Yiyang Gu, Xian‐Sheng Hua, Chong Chen, Yifan Wang, Minghua Deng, Yusheng Zhao and Meng Qu. Their work appears in journals such as Neural Networks, ACM Transactions on Knowledge Discovery from Data, IEEE Transactions on Multimedia, IEEE Transactions on Neural Networks and Learning Systems and ACM Transactions on Information Systems.
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.