Yonggan Fu
Impact in
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- Advanced Neural Network Applications
- Hardware and Architecture top 10%
- Parallel Computing and Optimization Techniques
Papers in
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- Domain Adaptation and Few-Shot Learning 8
- Adversarial Robustness in Machine Learning 6
- Stochastic Gradient Optimization Techniques 3
- Topic Modeling 3
- Neural Networks and Applications 2
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- Advanced Neural Network Applications 13
- Co-authors
- Yingyan Lin (30 shared papers)Chaojian Li (15 shared papers)Haoran You (14 shared papers)Zhongzhi Yu (11 shared papers)Yongan Zhang (11 shared papers)Zhangyang Wang (5 shared papers)Yue Wang (5 shared papers)Sixu Li (5 shared papers)
- Journals
- IEEE Micro (2 papers)ACM Journal on Emerging Technologies in Computing Systems (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)Chinese Archaeology (1 paper)2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits) (2 papers)
- Partner nations
- United StatesChinaIsrael
In The Last Decade
Yonggan Fu
33 papers receiving 299 citations
Peers
Comparison fields: 5 of 51
- Computer Vision and Pattern Recognition 131
- Hardware and Architecture 38
- Artificial Intelligence 167
- Computer Graphics and Computer-Aided Design 18
- Software 11
Countries citing papers authored by Yonggan Fu
This map shows the geographic impact of Yonggan Fu'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 Yonggan Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yonggan Fu more than expected).
Fields of papers citing papers by Yonggan Fu
This network shows the impact of papers produced by Yonggan Fu. 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 Yonggan Fu. The network helps show where Yonggan Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Yonggan Fu, 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 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 49 | |
| 2 | 2020 | 30 | |
| 3 | Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks | 2020 | 27 |
| 4 | 2020 | 26 | |
| 5 | 2023 | 21 | |
| 6 | 2021 | 17 | |
| 7 | 2024 | 16 | |
| 8 | 2024 | 14 | |
| 9 | 2022 | 13 | |
| 10 | 2021 | 13 | |
| 11 | 2022 | 11 | |
| 12 | 2021 | 8 | |
| 13 | 2024 | 7 | |
| 14 | 2022 | 6 | |
| 15 | 2021 | 6 | |
| 16 | Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference | 2021 | 5 |
| 17 | 2021 | 5 | |
| 18 | 2023 | 4 | |
| 19 | 2022 | 4 | |
| 20 | 2022 | 3 |
About Yonggan Fu
Yonggan Fu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Cardiology and Cardiovascular Medicine and Computational Mechanics, having authored 35 papers that have together received 305 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (13 papers), Domain Adaptation and Few-Shot Learning (8 papers), Adversarial Robustness in Machine Learning (6 papers), Advanced Memory and Neural Computing (4 papers), Stochastic Gradient Optimization Techniques (3 papers), CCD and CMOS Imaging Sensors (3 papers), Topic Modeling (3 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (131 citations), Hardware and Architecture (38 citations), Artificial Intelligence (167 citations), Computer Graphics and Computer-Aided Design (18 citations) and Software (11 citations). Yonggan Fu has collaborated with scholars based in United States, China and Israel. Frequent co-authors include Yingyan Lin, Chaojian Li, Haoran You, Zhongzhi Yu, Yongan Zhang, Zhangyang Wang, Yue Wang, Sixu Li, Cheng Wan and Yong-An Zhang. Their work appears in journals such as IEEE Micro, ACM Journal on Emerging Technologies in Computing Systems, IEEE Transactions on Neural Networks and Learning Systems, Chinese Archaeology and 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits).
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.