Yiping Ke

3.3k total citations
67 papers, 2.0k citations indexed

About

Yiping Ke is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Yiping Ke has authored 67 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Artificial Intelligence, 19 papers in Computer Vision and Pattern Recognition and 16 papers in Information Systems. Recurrent topics in Yiping Ke's work include Data Mining Algorithms and Applications (14 papers), Graph Theory and Algorithms (13 papers) and Domain Adaptation and Few-Shot Learning (13 papers). Yiping Ke is often cited by papers focused on Data Mining Algorithms and Applications (14 papers), Graph Theory and Algorithms (13 papers) and Domain Adaptation and Few-Shot Learning (13 papers). Yiping Ke collaborates with scholars based in Singapore, Hong Kong and China. Yiping Ke's co-authors include James Cheng, Wilfred Ng, Shumo Chu, Jeffrey Xu Yu, Linhong Zhu, Huanhuan Wu, Yi Wang, Hong Cheng, Pengfei Wei and Lu An and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Molecular Biology of the Cell and IEEE Transactions on Medical Imaging.

In The Last Decade

Yiping Ke

65 papers receiving 2.0k citations

Peers

Yiping Ke

SNP

CVPR

CNC

Lijun Chang Australia

Yixiang Fang China

Xin Huang China

Andrej Krevl Slovenia

Eui-Hong Han United States

Wilfred Ng Hong Kong

Prithviraj Sen United States

H.-P. Kriegel Germany

Francesco Gullo Italy

Tamás Sarlós United States

Lijun Chang Australia

Yiping Ke

1.2k ×1.3

753 ×1.0

SNP

950 ×1.5

CVPR

1.1k ×1.8

CNC

1.1k ×1.8

Citations per year, relative to Yiping Ke Yiping Ke (= 1×) peers Lijun Chang

Countries citing papers authored by Yiping Ke

Since Specialization

Citations

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

Fields of papers citing papers by Yiping Ke

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yiping Ke

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Ke, Yiping, et al.. (2025). Rethinking the message passing for graph-level classification tasks in a category-based view. Engineering Applications of Artificial Intelligence. 143. 109897–109897. 1 indexed citations

He, Kai, et al.. (2025). Multi-Atlas Brain Network Classification Through Consistency Distillation and Complementary Information Fusion. IEEE Journal of Biomedical and Health Informatics. 30(2). 1568–1579.

Xu, Jiaxing, et al.. (2024). Union Subgraph Neural Networks. Proceedings of the AAAI Conference on Artificial Intelligence. 38(14). 16173–16183. 3 indexed citations

Ke, Yiping, et al.. (2024). Corrections to “Contrastive Graph Pooling for Explainable Classification of Brain Networks”. IEEE Transactions on Medical Imaging. 43(11). 4075–4075. 1 indexed citations

He, Kai, et al.. (2024). Contrasformer: A Brain Network Contrastive Transformer for Neurodegenerative Condition Identification. 2671–2681. 2 indexed citations

Li, Tieying, et al.. (2024). Alleviating the Inconsistency of Multimodal Data in Cross-Modal Retrieval. DR-NTU (Nanyang Technological University). 4643–4656. 2 indexed citations

Wei, Pengfei, Yiping Ke, Yew-Soon Ong, & Zejun Ma. (2022). Adaptive Transfer Kernel Learning for Transfer Gaussian Process Regression. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(6). 7142–7156. 4 indexed citations

Wei, Pengfei, Yiping Ke, Xinghua Qu, & Tze-Yun Leong. (2021). Subdomain Adaptation With Manifolds Discrepancy Alignment. IEEE Transactions on Cybernetics. 52(11). 11698–11708. 19 indexed citations

Wei, Pengfei, Xinghua Qu, Yiping Ke, Tze-Yun Leong, & Yew-Soon Ong. (2020). Adaptive Knowledge Transfer based on Transfer Neural Kernel Network. Adaptive Agents and Multi-Agents Systems. 1485–1493. 1 indexed citations

10.

Wei, Pengfei, Ramón Sagarna, Yiping Ke, & Yew-Soon Ong. (2020). Easy-But-Effective Domain Sub-Similarity Learning for Transfer Regression. IEEE Transactions on Knowledge and Data Engineering. 34(9). 4161–4171. 5 indexed citations

11.

Wei, Pengfei, Ramón Sagarna, Yiping Ke, & Yew-Soon Ong. (2020). Practical Multisource Transfer Regression With Source–Target Similarity Captures. IEEE Transactions on Neural Networks and Learning Systems. 32(8). 3498–3509. 3 indexed citations

12.

Li, Tianbo & Yiping Ke. (2019). Thinning for Accelerating the Learning of Point Processes. Neural Information Processing Systems. 32. 4091–4101. 1 indexed citations

13.

Wei, Pengfei, Ramón Sagarna, Yiping Ke, & Yew-Soon Ong. (2018). Uncluttered Domain Sub-Similarity Modeling for Transfer Regression. DR-NTU (Nanyang Technological University). 1314–1319. 8 indexed citations

14.

Ke, Yiping, et al.. (2017). A Fast Algorithm for Matrix Eigen-decompositionn.. Uncertainty in Artificial Intelligence. 2 indexed citations

15.

Hussain, Shaista, Xavier Le Guezennec, Yi Wang, et al.. (2017). Digging deep into Golgi phenotypic diversity with unsupervised machine learning. Molecular Biology of the Cell. 28(25). 3686–3698. 7 indexed citations

16.

Wei, Pengfei, Yiping Ke, & Chi-Keong Goh. (2016). Deep nonlinear feature coding for unsupervised domain adaptation. International Joint Conference on Artificial Intelligence. 2189–2195. 33 indexed citations

17.

Wu, Huanhuan, James Cheng, Yi Lu, et al.. (2015). Core decomposition in large temporal graphs. 649–658. 51 indexed citations

18.

Zhu, Yuanyuan, Lu Qin, Jeffrey Xu Yu, Yiping Ke, & Xuemin Lin. (2012). High efficiency and quality: large graphs matching. The VLDB Journal. 22(3). 345–368. 21 indexed citations

19.

Cheng, James, Yiping Ke, Ada Wai-Chee Fu, Jeffrey Xu Yu, & Linhong Zhu. (2011). Finding maximal cliques in massive networks. ACM Transactions on Database Systems. 36(4). 1–34. 100 indexed citations

20.

Cheng, Hong, et al.. (2010). Stock risk mining by news. Australasian Database Conference. 179–188. 1 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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