Linchuan Xu

605 total citations
31 papers, 384 citations indexed

About

Linchuan Xu is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Linchuan Xu has authored 31 papers receiving a total of 384 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 14 papers in Statistical and Nonlinear Physics and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Linchuan Xu's work include Advanced Graph Neural Networks (16 papers), Complex Network Analysis Techniques (14 papers) and Text and Document Classification Technologies (7 papers). Linchuan Xu is often cited by papers focused on Advanced Graph Neural Networks (16 papers), Complex Network Analysis Techniques (14 papers) and Text and Document Classification Technologies (7 papers). Linchuan Xu collaborates with scholars based in Hong Kong, United States and Japan. Linchuan Xu's co-authors include Philip S. Yu, Xiaokai Wei, Jiannong Cao, Kenji Yamanishi, Bokai Cao, Jun Huang, Jing Wang, Ryo Asaoka, Hiroshi Murata and Xiao Huang and has published in prestigious journals such as SHILAP Revista de lepidopterología, American Journal of Ophthalmology and Neurocomputing.

In The Last Decade

Linchuan Xu

30 papers receiving 379 citations

Peers

Linchuan Xu

SNP

CVPR

Nian Liu China

Daokun Zhang Australia

Chunjie Wang China

Mehrnoush Mohammadi Australia

Yujie Mo China

S. K. Setua India

Dingyuan Zhu China

Ke Tu China

Chaoqi Yang United States

Nian Liu China

Linchuan Xu

316 ×1.1

97 ×0.6

SNP

147 ×2.0

69 ×1.0

CVPR

28 ×0.5

Citations per year, relative to Linchuan Xu Linchuan Xu (= 1×) peers Nian Liu

Countries citing papers authored by Linchuan Xu

Since Specialization

Citations

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

Fields of papers citing papers by Linchuan Xu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Linchuan Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Linchuan Xu. A scholar is included among the top collaborators of Linchuan Xu 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 Linchuan Xu. Linchuan Xu 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

Xu, Linchuan, et al.. (2024). GMMDA: Gaussian mixture modeling of graph in latent space for graph data augmentation. Knowledge and Information Systems. 66(12). 7667–7695. 1 indexed citations

Che, Hao, et al.. (2023). Multi-layered semantic representation network for multi-label image classification. International Journal of Machine Learning and Cybernetics. 14(10). 3427–3435. 14 indexed citations

Xu, Linchuan, et al.. (2023). GMMDA: Gaussian Mixture Modeling of Graph in Latent Space for Graph Data Augmentation. 34. 319–328.

Huang, Xiao, et al.. (2022). Contrastive Knowledge Graph Error Detection. Proceedings of the 31st ACM International Conference on Information & Knowledge Management. 2590–2599. 23 indexed citations

Xu, Linchuan, et al.. (2022). RGB Color Model Aware Computational Color Naming and Its Application to Data Augmentation. 2022 IEEE International Conference on Big Data (Big Data). 1172–1181. 2 indexed citations

Xu, Linchuan, et al.. (2022). Network Change Detection Based on Random Walk in Latent Space. IEEE Transactions on Knowledge and Data Engineering. 1–1. 3 indexed citations

Wang, Jing, et al.. (2021). Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 34. 2 indexed citations

Asaoka, Ryo, Linchuan Xu, Hiroshi Murata, et al.. (2021). A Joint Multitask Learning Model for Cross-sectional and Longitudinal Predictions of Visual Field Using OCT. SHILAP Revista de lepidopterología. 1(4). 100055–100055. 10 indexed citations

Xu, Linchuan, et al.. (2021). PAMI: A Computational Module for Joint Estimation and Progression Prediction of Glaucoma. 3826–3834. 1 indexed citations

10.

Huang, Jun, et al.. (2021). Multi-label learning with missing and completely unobserved labels. Data Mining and Knowledge Discovery. 35(3). 1061–1086. 20 indexed citations

11.

Xu, Linchuan, Ryo Asaoka, Hiroshi Murata, et al.. (2020). Predicting the Glaucomatous Central 10-Degree Visual Field From Optical Coherence Tomography Using Deep Learning and Tensor Regression. American Journal of Ophthalmology. 218. 304–313. 23 indexed citations

12.

Xu, Linchuan, Ryo Asaoka, Hiroshi Murata, et al.. (2020). Improving Visual Field Trend Analysis with OCT and Deeply Regularized Latent-Space Linear Regression. Ophthalmology Glaucoma. 4(1). 78–88. 3 indexed citations

13.

Li, Wei, Linchuan Xu, Zhixuan Liang, et al.. (2020). Sketch-then-Edit Generative Adversarial Network. Knowledge-Based Systems. 203. 106102–106102. 14 indexed citations

14.

Xu, Linchuan, et al.. (2019). Glaucoma Progression Prediction Using Retinal Thickness via Latent Space Linear Regression. Greenwich Academic Literature Archive (University of Greenwich). 2278–2286. 9 indexed citations

15.

Wang, Jing, et al.. (2019). Attributed Subspace Clustering. Bournemouth University Research Online (Bournemouth University). 3719–3725. 3 indexed citations

16.

Xu, Linchuan, Jiannong Cao, Xiaokai Wei, & Philip S. Yu. (2019). Network Embedding via Coupled Kernelized Multi-Dimensional Array Factorization. IEEE Transactions on Knowledge and Data Engineering. 32(12). 2414–2425. 9 indexed citations

17.

Xu, Linchuan, Xiaokai Wei, Jiannong Cao, & Philip S. Yu. (2018). On Learning Community-specific Similarity Metrics for Cold-start Link Prediction. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 9. 1–8. 2 indexed citations

18.

Xu, Linchuan, Xiaokai Wei, Jiannong Cao, & Philip S. Yu. (2018). On Exploring Semantic Meanings of Links for Embedding Social Networks. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 479–488. 21 indexed citations

19.

Xu, Linchuan, Xiaokai Wei, Jiannong Cao, & Philip S. Yu. (2018). Multi-task network embedding. International Journal of Data Science and Analytics. 8(2). 183–198. 13 indexed citations

20.

Xu, Linchuan, Xiaokai Wei, Jiannong Cao, & Philip S. Yu. (2017). Embedding of Embedding (EOE). PolyU Institutional Research Archive (Hong Kong Polytechnic University). 741–749. 99 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.

Explore authors with similar magnitude of impact