Jinyu Cai

477 total citations
21 papers, 315 citations indexed

About

Jinyu Cai is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Jinyu Cai has authored 21 papers receiving a total of 315 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 11 papers in Computer Vision and Pattern Recognition and 2 papers in Computer Networks and Communications. Recurrent topics in Jinyu Cai's work include Anomaly Detection Techniques and Applications (6 papers), Generative Adversarial Networks and Image Synthesis (5 papers) and Face and Expression Recognition (4 papers). Jinyu Cai is often cited by papers focused on Anomaly Detection Techniques and Applications (6 papers), Generative Adversarial Networks and Image Synthesis (5 papers) and Face and Expression Recognition (4 papers). Jinyu Cai collaborates with scholars based in China, Singapore and Macao. Jinyu Cai's co-authors include Shiping Wang, Wenzhong Guo, Jicong Fan, Zhao Zhang, Renjie Lin, Yiliang Lin, Hong Xue, Hong Xue, See-Kiong Ng and Pengyang Wang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Expert Systems with Applications and Pattern Recognition.

In The Last Decade

Jinyu Cai

18 papers receiving 310 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jinyu Cai China	7	204	160	39	26	18	21	315
Jiming Liu China	8	290 1.4×	236 1.5×	47 1.2×	30 1.2×	44 2.4×	16	422
Qingsheng Ren China	8	220 1.1×	125 0.8×	21 0.5×	34 1.3×	16 0.9×	20	305
Litao Yu Australia	8	174 0.9×	262 1.6×	14 0.4×	18 0.7×	38 2.1×	27	399
Chao Lan United States	11	151 0.7×	148 0.9×	26 0.7×	72 2.8×	44 2.4×	43	325
Huayi Tang China	6	336 1.6×	370 2.3×	27 0.7×	32 1.2×	41 2.3×	9	544
Meiyu Liang China	11	215 1.1×	198 1.2×	32 0.8×	18 0.7×	33 1.8×	63	384
Shide Du China	11	231 1.1×	219 1.4×	26 0.7×	14 0.5×	33 1.8×	28	345
Lele Fu China	10	271 1.3×	290 1.8×	37 0.9×	25 1.0×	45 2.5×	27	464
Bassoma Diallo China	8	168 0.8×	196 1.2×	11 0.3×	28 1.1×	35 1.9×	12	300
Kaiyang Liao China	8	96 0.5×	193 1.2×	22 0.6×	13 0.5×	47 2.6×	35	277

Countries citing papers authored by Jinyu Cai

Since Specialization

Citations

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

Fields of papers citing papers by Jinyu Cai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jinyu Cai

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

Cai, Jinyu, et al.. (2025). discDC: Unsupervised discriminative deep image clustering via confidence-driven self-labeling. Pattern Recognition. 172. 112382–112382.

Cai, Jinyu, et al.. (2025). MoEGAD: A Mixture-of-Experts Framework With Pseudo-Anomaly Generation for Graph-Level Anomaly Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence. 48(4). 4473–4489.

Cai, Jinyu, et al.. (2025). Mixture of Experts as Representation Learner for Deep Multi-View Clustering. Proceedings of the AAAI Conference on Artificial Intelligence. 39(21). 22704–22713. 2 indexed citations

Cai, Jinyu, et al.. (2024). Deep Masked Graph Node Clustering. IEEE Transactions on Computational Social Systems. 11(6). 7257–7270. 3 indexed citations

Xu, Jinglue, et al.. (2024). Automatic Adaptation Rule Optimization via Large Language Models. 180–181.

Cai, Jinyu, et al.. (2024). Towards Effective Federated Graph Anomaly Detection via Self-boosted Knowledge Distillation. 5537–5546. 2 indexed citations

Cai, Jinyu, et al.. (2024). Towards Efficient Discrete Controller Synthesis: Semantics-Aware Stepwise Policy Design via LLM. 1–4. 3 indexed citations

Cai, Jinyu, et al.. (2024). Deep graph-level clustering using pseudo-label-guided mutual information maximization network. Neural Computing and Applications. 36(16). 9551–9566. 3 indexed citations

Cai, Jinyu, et al.. (2024). Wasserstein Embedding Learning for Deep Clustering: A Generative Approach. IEEE Transactions on Multimedia. 26. 7567–7580. 19 indexed citations

10.

Lin, Renjie, et al.. (2023). Label correction using contrastive prototypical classifier for noisy label learning. Information Sciences. 649. 119647–119647. 5 indexed citations

11.

Cai, Jinyu, et al.. (2022). Efficient Deep Embedded Subspace Clustering. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 21–30. 77 indexed citations

12.

Cai, Jinyu, et al.. (2021). Unsupervised deep clustering via contractive feature representation and focal loss. Pattern Recognition. 123. 108386–108386. 58 indexed citations

13.

Cai, Jinyu, Shiping Wang, & Wenzhong Guo. (2021). Unsupervised embedded feature learning for deep clustering with stacked sparse auto-encoder. Expert Systems with Applications. 186. 115729–115729. 36 indexed citations

14.

Lin, Renjie, et al.. (2021). Deep image clustering by fusing contrastive learning and neighbor relation mining. Knowledge-Based Systems. 238. 107967–107967. 28 indexed citations

15.

Guo, Wenzhong, Jinyu Cai, & Shiping Wang. (2019). Unsupervised discriminative feature representation via adversarial auto-encoder. Applied Intelligence. 50(4). 1155–1171. 16 indexed citations

16.

Wang, Shiping, et al.. (2019). An Overview of Unsupervised Deep Feature Representation for Text Categorization. IEEE Transactions on Computational Social Systems. 6(3). 504–517. 48 indexed citations

17.

Cai, Jinyu, Shiping Wang, & Wenzhong Guo. (2019). Unsupervised deep feature representation using adversarial auto-encoder. 7. 749–754. 2 indexed citations

18.

Cai, Jinyu, Shiping Wang, & Wenzhong Guo. (2019). Stacked Sparse Auto-Encoder for Deep Clustering. 7. 1532–1538. 2 indexed citations

19.

Xue, Hong, et al.. (2017). The collaborative decision of profit distribution in retail supply chain under emergency. 18. 3385–3389. 2 indexed citations

20.

Xue, Hong, et al.. (2017). Early warning decision-making system based on cloud computing technology for retail supply chain unconventional emergency. 224–229. 3 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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