Kaichao You

1.8k total citations · 1 hit paper
11 papers, 673 citations indexed

About

Kaichao You is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Kaichao You has authored 11 papers receiving a total of 673 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 3 papers in Electrical and Electronic Engineering. Recurrent topics in Kaichao You's work include Domain Adaptation and Few-Shot Learning (5 papers), Multimodal Machine Learning Applications (4 papers) and Advanced Memory and Neural Computing (3 papers). Kaichao You is often cited by papers focused on Domain Adaptation and Few-Shot Learning (5 papers), Multimodal Machine Learning Applications (4 papers) and Advanced Memory and Neural Computing (3 papers). Kaichao You collaborates with scholars based in China, United States and Hong Kong. Kaichao You's 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 and has published in prestigious journals such as Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.

In The Last Decade

Kaichao You

11 papers receiving 660 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Universal Domain Adaptation

2019 303 citations Kaichao You, Mingsheng Long et al. profile →

Peers

Countries citing papers authored by Kaichao You

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Kaichao You

This figure shows the co-authorship network connecting the top 25 collaborators of Kaichao You. A scholar is included among the top collaborators of Kaichao You based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kaichao You. Kaichao You is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

#	Work	Indexed citations
1	Neuromorphic-enabled video-activated cell sorting 2024 ·Nature Communications ·Weihua He, Junwen Zhu, Yongxiang Feng, Fei Liang, Kaichao You, Huichao Chai, (unknown), (unknown), (unknown), Jingjing Zhao, Lei Deng, Rong Zhao, Wenhui Wang	28
2	Event-Based Semantic Segmentation With Posterior Attention 2023 ·IEEE Transactions on Image Processing ·(unknown), Kaichao You, Weihua He, (unknown), (unknown), Yaoyuan Wang, Xu Jia, Yihang Lou, Jingyi Zhang, Guoqi Li, Ziyang Zhang	20
3	From Big to Small: Adaptive Learning to Partial-Set Domains 2022 ·IEEE Transactions on Pattern Analysis and Machine Intelligence ·Zhangjie Cao, Kaichao You, Ziyang Zhang, Jianmin Wang, Mingsheng Long	24
4	TimeReplayer: Unlocking the Potential of Event Cameras for Video Interpolation 2022 ·2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) ·Weihua He, Kaichao You, (unknown), Jia Xu, Ziyang Zhang, Wenhui Wang, Huchuan Lu, Yaoyuan Wang, Jianxing Liao	21
5	LogME: Practical Assessment of Pre-trained Models for Transfer Learning 2021 ·Kaichao You, Yong Liu, Jianmin Wang, Mingsheng Long	2
6	Co-Tuning for Transfer Learning 2020 ·Neural Information Processing Systems ·Kaichao You, (unknown), Mingsheng Long, Jianmin Wang	29
7	Stochastic Normalization 2020 ·Neural Information Processing Systems ·(unknown), Kaichao You, Mingsheng Long, Jianmin Wang	17
8	Learning Stages: Phenomenon, Root Cause, Mechanism Hypothesis, and Implications. 2019 ·arXiv (Cornell University) ·Kaichao You, Mingsheng Long, Michael I. Jordan, Jianmin Wang	4
9	Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation. 2019 ·International Conference on Machine Learning ·Kaichao You, Ximei Wang, Mingsheng Long, Michael I. Jordan	46
10	Learning to Transfer Examples for Partial Domain Adaptation 2019 ·Rare & Special e-Zone (The Hong Kong University of Science and Technology) ·Zhangjie Cao, Kaichao You, Mingsheng Long, Jianmin Wang, Qiang Yang	179
11	Universal Domain Adaptation breakdown → 2019 ·Kaichao You, Mingsheng Long, Zhangjie Cao, Jianmin Wang, Michael I. Jordan	303

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.

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