Shujian Yu

1.7k total citations
66 papers, 872 citations indexed

About

Shujian Yu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Shujian Yu has authored 66 papers receiving a total of 872 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 25 papers in Computer Vision and Pattern Recognition and 14 papers in Signal Processing. Recurrent topics in Shujian Yu's work include Blind Source Separation Techniques (11 papers), Neural Networks and Applications (10 papers) and Face and Expression Recognition (9 papers). Shujian Yu is often cited by papers focused on Blind Source Separation Techniques (11 papers), Neural Networks and Applications (10 papers) and Face and Expression Recognition (9 papers). Shujian Yu collaborates with scholars based in China, United States and Norway. Shujian Yu's co-authors include José C. Prı́ncipe, Badong Chen, Robert Jenssen, Xinge You, Weihua Ou, Xinge You, Dacheng Tao, Yi Mou, Kaizhong Zheng and Xiao‐Yuan Jing and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and NeuroImage.

In The Last Decade

Shujian Yu

64 papers receiving 848 citations

Peers

Shujian Yu

AI

CVPR

SP

CM

MT

Dana Lahat France

Carlos Alzate Belgium

SugiyamaMasashi

Cheong Hee Park South Korea

Lai Wei China

Li Zhao China

Robert J. Schalkoff United States

Jian‐Xun Mi China

Bharat Richhariya India

Dana Lahat France

Shujian Yu

247 ×0.7

AI

171 ×0.5

CVPR

186 ×1.3

SP

63 ×0.6

CM

67 ×0.7

MT

Citations per year, relative to Shujian Yu Shujian Yu (= 1×) peers Dana Lahat

Countries citing papers authored by Shujian Yu

Since Specialization

Citations

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

Fields of papers citing papers by Shujian Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shujian Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Shujian Yu. A scholar is included among the top collaborators of Shujian Yu 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 Shujian Yu. Shujian Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Yu, Shujian, et al.. (2025). An information bottleneck approach for feature selection. Pattern Recognition. 164. 111564–111564. 1 indexed citations

2.

Ma, Z. & Shujian Yu. (2025). Cauchy-Schwarz Divergence Transfer Entropy. VU Research Portal. 1–5.

3.

Lv, Feiya, Borui Yang, Shujian Yu, et al.. (2025). A unified model integrating Granger causality-based causal discovery and fault diagnosis in chemical processes. Computers & Chemical Engineering. 196. 109028–109028. 5 indexed citations

4.

Yu, Shujian, et al.. (2025). The Conditional Cauchy-Schwarz Divergence With Applications to Time-Series Data and Sequential Decision Making. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(7). 5901–5917. 1 indexed citations

5.

Zheng, Kaizhong, et al.. (2024). BPI-GNN: Interpretable brain network-based psychiatric diagnosis and subtyping. NeuroImage. 292. 120594–120594. 9 indexed citations

6.

Gong, Tieliang, et al.. (2023). Optimal Randomized Approximations for Matrix-Based Rényi’s Entropy. IEEE Transactions on Information Theory. 69(7). 4218–4234. 2 indexed citations

7.

Yu, Shujian, et al.. (2023). Causal Recurrent Variational Autoencoder for Medical Time Series Generation. Proceedings of the AAAI Conference on Artificial Intelligence. 37(7). 8562–8570. 37 indexed citations

8.

Yu, Shujian. (2023). The Analysis of Deep Neural Networks by Information Theory: From Explainability to Generalization. Proceedings of the AAAI Conference on Artificial Intelligence. 37(13). 15462–15462. 1 indexed citations

9.

Li, Qiang, Greg Ver Steeg, Shujian Yu, & Jesús Malo. (2022). Functional Connectome of the Human Brain with Total Correlation. Entropy. 24(12). 1725–1725. 12 indexed citations

10.

Gong, Tieliang, et al.. (2022). Computationally Efficient Approximations for Matrix-Based Rényi's Entropy. IEEE Transactions on Signal Processing. 70. 6170–6184. 2 indexed citations

11.

Li, Hongming, Shujian Yu, & José C. Prı́ncipe. (2022). Deep Deterministic Independent Component Analysis for Hyperspectral Unmixing. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 3878–3882. 3 indexed citations

12.

Yu, Xi, Shujian Yu, & José C. Prı́ncipe. (2021). Deep Deterministic Information Bottleneck with Matrix-Based Entropy Functional. 3160–3164. 13 indexed citations

13.

Lv, Feiya, Shujian Yu, Chenglin Wen, & José C. Prı́ncipe. (2020). Mutual Information Matrix for Interpretable Fault Detection.. arXiv (Cornell University). 1 indexed citations

14.

Yu, Shujian, et al.. (2019). Multiview Hybrid Embedding: A Divide-and-Conquer Approach. IEEE Transactions on Cybernetics. 50(8). 3640–3653. 13 indexed citations

15.

Yu, Shujian & José C. Prı́ncipe. (2019). Understanding autoencoders with information theoretic concepts. Neural Networks. 117. 104–123. 90 indexed citations

16.

Yu, Shujian, et al.. (2018). Marine Animal Classification With Correntropy-Loss-Based Multiview Learning. IEEE Journal of Oceanic Engineering. 44(4). 1116–1129. 3 indexed citations

17.

Yu, Shujian, Robert Jenssen, & José C. Prı́ncipe. (2018). Understanding Convolutional Neural Network Training with Information Theory.. arXiv (Cornell University). 6 indexed citations

18.

You, Xinge, et al.. (2016). Mixed-norm partial least squares. Chemometrics and Intelligent Laboratory Systems. 152. 42–53. 3 indexed citations

19.

Yu, Shujian, et al.. (2016). Multiple adaptive kernel size KLMS for Beijing PM2.5 prediction. 471. 1403–1407. 3 indexed citations

20.

Mou, Yi, et al.. (2013). Regularized multivariate scatter correction. Chemometrics and Intelligent Laboratory Systems. 132. 168–174. 17 indexed citations

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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