Jun Zhu

202 papers and 8.0k indexed citations i.

About

Jun Zhu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Jun Zhu has authored 202 papers receiving a total of 8.0k indexed citations (citations by other indexed papers that have themselves been cited), including 136 papers in Artificial Intelligence, 90 papers in Computer Vision and Pattern Recognition and 23 papers in Signal Processing. Recurrent topics in Jun Zhu’s work include Domain Adaptation and Few-Shot Learning (34 papers), Adversarial Robustness in Machine Learning (29 papers) and Bayesian Methods and Mixture Models (25 papers). Jun Zhu is often cited by papers focused on Domain Adaptation and Few-Shot Learning (34 papers), Adversarial Robustness in Machine Learning (29 papers) and Bayesian Methods and Mixture Models (25 papers). Jun Zhu collaborates with scholars based in China, United States and United Kingdom. Jun Zhu's co-authors include Pawel A. Penczek, Yanhong Li, Michael Radermacher, Joachim Frank, A. Leith, Eric P. Xing, Hang Su, Yinpeng Dong, Shi‐Xia Liu and Yujie Wu and has published in prestigious journals such as Nature, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.

In The Last Decade

Co-authorship network of co-authors of Jun Zhu i

Fields of papers citing papers by Jun Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun Zhu. 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 Jun Zhu. The network helps show where Jun Zhu may publish in the future.

Countries citing papers authored by Jun Zhu

Since Specialization
Citations

This map shows the geographic impact of Jun Zhu'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 Jun Zhu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Zhu more than expected).

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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