Kaichao You
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- Multimodal Machine Learning Applications 4
- Artificial Intelligence top 5%
- Domain Adaptation and Few-Shot Learning 5
- Machine Learning and ELM 2
- Neural Networks and Applications 1
- Media Technology top 10%
- Control and Systems Engineering top 10%
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- Advanced Memory and Neural Computing 3
- CCD and CMOS Imaging Sensors 1
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- COVID-19 diagnosis using AI 2
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- Neural dynamics and brain function 1
- Co-authors
- Mingsheng LongJianmin WangZhangjie CaoMichael I. JordanQiang YangXimei WangWeihua HeZiyang Zhang
- Journals
- Nature Communications (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)IEEE Transactions on Image Processing (1 paper)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Kaichao You
11 papers receiving 660 citations
Hit Papers
Peers
Comparison fields: 5 of 87
- Computer Vision and Pattern Recognition 341
- Artificial Intelligence 463
- Media Technology 36
- Cancer Research 54
- Control and Systems Engineering 76
Countries citing papers authored by Kaichao You
This map shows the geographic impact of Kaichao You'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 Kaichao You with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaichao You more than expected).
Fields of papers citing papers by Kaichao You
This network shows the impact of papers produced by Kaichao You. 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 Kaichao You. The network helps show where Kaichao You may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kaichao You, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 28 | |
| 2 | 2023 | 20 | |
| 3 | 2022 | 24 | |
| 4 | 2022 | 21 | |
| 5 | LogME: Practical Assessment of Pre-trained Models for Transfer Learning | 2021 | 2 |
| 6 | Co-Tuning for Transfer Learning | 2020 | 29 |
| 7 | Stochastic Normalization | 2020 | 17 |
| 8 | Learning Stages: Phenomenon, Root Cause, Mechanism Hypothesis, and Implications. | 2019 | 4 |
| 9 | Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation. | 2019 | 46 |
| 10 | 2019 | 179 | |
| 11 | Universal Domain Adaptationbreakdown → | 2019 | 303 |
About Kaichao You
Kaichao You is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biophysics, having authored 11 papers that have together received 673 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (5 papers), Multimodal Machine Learning Applications (4 papers), Advanced Memory and Neural Computing (3 papers), Machine Learning and ELM (2 papers), COVID-19 diagnosis using AI (2 papers), Neural dynamics and brain function (1 paper), Neural Networks and Applications (1 paper) and CCD and CMOS Imaging Sensors (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (341 citations), Artificial Intelligence (463 citations) and Media Technology (36 citations). Kaichao You has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Mingsheng Long, Jianmin Wang, Zhangjie Cao, Michael I. Jordan, Qiang Yang, Ximei Wang, Weihua He, Ziyang Zhang, Yaoyuan Wang and Wenhui Wang. Their work appears in journals such as Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.
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.