Wenchao Yu

1.9k total citations · 1 hit paper
27 papers, 1.0k citations indexed

About

Wenchao Yu is a scholar working on Artificial Intelligence, Information Systems and Statistical and Nonlinear Physics. According to data from OpenAlex, Wenchao Yu has authored 27 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 4 papers in Information Systems and 4 papers in Statistical and Nonlinear Physics. Recurrent topics in Wenchao Yu's work include Advanced Graph Neural Networks (10 papers), Explainable Artificial Intelligence (XAI) (5 papers) and Machine Learning in Healthcare (4 papers). Wenchao Yu is often cited by papers focused on Advanced Graph Neural Networks (10 papers), Explainable Artificial Intelligence (XAI) (5 papers) and Machine Learning in Healthcare (4 papers). Wenchao Yu collaborates with scholars based in United States, China and Japan. Wenchao Yu's co-authors include Wei Wang, Wei Cheng, Haifeng Chen, Charų C. Aggarwal, Bo Zong, Jingchao Ni, Kai Zhang, Dongjin Song, Dongsheng Luo and X. D. Zhang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Neurocomputing and British Journal of Dermatology.

In The Last Decade

Wenchao Yu

25 papers receiving 980 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Learning to Drop: Robust Graph Neural Network via Topological Denoising

2021 156 citations Dongsheng Luo, Wei Cheng et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Wenchao Yu United States	13	766	274	168	151	131	27	1.0k
Hwanjo Yu South Korea	16	731 1.0×	172 0.6×	158 0.9×	169 1.1×	150 1.1×	42	1.1k
Dawei Zhou United States	15	355 0.5×	158 0.6×	58 0.3×	134 0.9×	65 0.5×	44	649
Rik Sarkar United Kingdom	16	342 0.4×	184 0.7×	61 0.4×	133 0.9×	383 2.9×	33	1.1k
Sayan Ghosh United States	14	408 0.5×	97 0.4×	59 0.4×	144 1.0×	119 0.9×	72	802
Sangwook Kim South Korea	10	193 0.3×	369 1.3×	76 0.5×	127 0.8×	154 1.2×	58	761
Lianhua Chi Australia	16	373 0.5×	68 0.2×	85 0.5×	136 0.9×	133 1.0×	57	669
Yasuko Matsubara Japan	11	328 0.4×	208 0.8×	81 0.5×	59 0.4×	55 0.4×	40	669
Marco Maggini Italy	21	763 1.0×	116 0.4×	222 1.3×	457 3.0×	88 0.7×	84	1.4k
Cong Wang China	18	420 0.5×	64 0.2×	180 1.1×	159 1.1×	227 1.7×	99	894

Countries citing papers authored by Wenchao Yu

Since Specialization

Citations

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

Fields of papers citing papers by Wenchao Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wenchao Yu

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

1.

Jiang, Yushan, Jingchao Ni, Wenchao Yu, et al.. (2025). Multi-modal Time Series Analysis: A Tutorial and Survey. 6043–6053. 4 indexed citations

2.

Wang, Xinyuan, Yanchi Liu, Wei Cheng, et al.. (2025). MixLLM: Dynamic Routing in Mixed Large Language Models. 10912–10922. 1 indexed citations

3.

Luo, Dongsheng, Tianxiang Zhao, Wei Cheng, et al.. (2024). Towards Inductive and Efficient Explanations for Graph Neural Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(8). 5245–5259. 6 indexed citations

4.

Zhao, Tianxiang, Wenchao Yu, Suhang Wang, et al.. (2024). Interpretable Imitation Learning with Dynamic Causal Relations. 967–975.

5.

Luo, Dongsheng, Wei Cheng, Yingheng Wang, et al.. (2023). Time Series Contrastive Learning with Information-Aware Augmentations. Proceedings of the AAAI Conference on Artificial Intelligence. 37(4). 4534–4542. 47 indexed citations

6.

Jiang, Yushan, Wenchao Yu, Dongjin Song, Wei Cheng, & Haifeng Chen. (2023). Interpretable Skill Learning for Dynamic Treatment Regimes through Imitation. 1–6. 1 indexed citations

7.

Zhao, Tianxiang, Wenchao Yu, Suhang Wang, et al.. (2023). Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. arXiv (Cornell University). 3513–3524. 1 indexed citations

8.

Jiang, Yushan, Wenchao Yu, Dongjin Song, et al.. (2023). FedSkill: Privacy Preserved Interpretable Skill Learning via Imitation. 1010–1019. 3 indexed citations

9.

Zhao, Xujiang, Xuchao Zhang, Wei Cheng, et al.. (2022). Seed: Sound Event Early Detection Via Evidential Uncertainty. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 3618–3622. 7 indexed citations

10.

Luo, Dongsheng, Wei Cheng, Wenchao Yu, et al.. (2021). Learning to Drop: Robust Graph Neural Network via Topological Denoising. 779–787. 156 indexed citations breakdown →

11.

Wang, Lichen, Bo Zong, Wei Cheng, et al.. (2020). Inductive and Unsupervised Representation Learning on Graph Structured Objects. International Conference on Learning Representations. 6 indexed citations

12.

Xu, Dongkuan, Wei Cheng, Bo Zong, et al.. (2020). Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series. Proceedings of the AAAI Conference on Artificial Intelligence. 34(2). 1395–1402. 31 indexed citations

13.

Zheng, Cheng, Bo Zong, Wei Cheng, et al.. (2020). Robust Graph Representation Learning via Neural Sparsification. 1. 11458–11468. 51 indexed citations

14.

Wang, Lu, Wenchao Yu, Xiaofeng He, et al.. (2020). Adversarial Cooperative Imitation Learning for Dynamic Treatment Regimes✱. 1785–1795. 16 indexed citations

15.

Wang, Yan, Wenchao Yu, Sam Liu, & Sean D. Young. (2019). The Relationship Between Social Media Data and Crime Rates in the United States. Social Media + Society. 5(1). 4 indexed citations

16.

Yu, Wenchao, Cheng Zheng, Wei Cheng, et al.. (2018). Learning Deep Network Representations with Adversarially Regularized Autoencoders. 2663–2671. 131 indexed citations

17.

Yu, Wenchao, Wei Cheng, Charų C. Aggarwal, Haifeng Chen, & Wei Wang. (2017). Link Prediction with Spatial and Temporal Consistency in Dynamic Networks. 3343–3349. 52 indexed citations

18.

Yu, Wenchao, Fuzhen Zhuang, Qing He, & Zhongzhi Shi. (2014). Learning deep representations via extreme learning machines. Neurocomputing. 149. 308–315. 87 indexed citations

19.

Liu, Zitao, et al.. (2010). A feature selection method for document clustering based on part-of-speech and word co-occurrence. 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery. 2331–2334. 8 indexed citations

20.

Yu, Wenchao. (2009). The Extraction of Tag Information in Flash Animation. Computer Knowledge and Technology. 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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