Yaochen Xie

1.6k total citations · 2 hit papers
19 papers, 972 citations indexed

About

Yaochen Xie is a scholar working on Artificial Intelligence, Information Systems and Media Technology. According to data from OpenAlex, Yaochen Xie has authored 19 papers receiving a total of 972 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 4 papers in Information Systems and 4 papers in Media Technology. Recurrent topics in Yaochen Xie's work include Image Processing Techniques and Applications (4 papers), Text and Document Classification Technologies (3 papers) and Topic Modeling (3 papers). Yaochen Xie is often cited by papers focused on Image Processing Techniques and Applications (4 papers), Text and Document Classification Technologies (3 papers) and Topic Modeling (3 papers). Yaochen Xie collaborates with scholars based in United States and China. Yaochen Xie's co-authors include Shuiwang Ji, Zhengyang Wang, Xu Zhao, Hongjun Mao, Jianjun He, Lin Wu, Taosheng Jin, Congbo Song, Qili Dai and Baoshuang Liu and has published in prestigious journals such as Bioinformatics, IEEE Transactions on Pattern Analysis and Machine Intelligence and Environmental Pollution.

In The Last Decade

Yaochen Xie

16 papers receiving 961 citations

Hit Papers

Air pollution in China: Status and spatiotemporal variations 2017 2026 2020 2023 2017 2022 100 200 300 400 500
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.

  1. Air pollution in China: Status and spatiotemporal variations
    2017 538 citations Congbo Song, Lin Wu et al. Environmental Pollution profile →
  2. Self-Supervised Learning of Graph Neural Networks: A Unified Review
    2022 216 citations Yaochen Xie, Xu Zhao et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yaochen Xie United States 9 449 266 251 212 124 19 972
Pengfei Li China 20 276 0.6× 240 0.9× 130 0.5× 167 0.8× 149 1.2× 76 1.1k
Xianneng Li China 16 211 0.5× 97 0.4× 219 0.9× 272 1.3× 47 0.4× 57 883
Juanjuan Zhao China 20 237 0.5× 70 0.3× 147 0.6× 88 0.4× 226 1.8× 68 1.4k
Yichen Wang China 26 710 1.6× 605 2.3× 240 1.0× 84 0.4× 443 3.6× 152 2.4k
Da Gao China 15 309 0.7× 468 1.8× 198 0.8× 269 1.3× 233 1.9× 37 1.1k
Zhiqiang Liu China 15 417 0.9× 163 0.6× 260 1.0× 135 0.6× 536 4.3× 53 987
Liqun Liu China 15 332 0.7× 79 0.3× 157 0.6× 181 0.9× 90 0.7× 65 979
Can Liu China 19 331 0.7× 378 1.4× 211 0.8× 96 0.5× 83 0.7× 140 995
Shaofu Lin China 12 105 0.2× 61 0.2× 166 0.7× 213 1.0× 53 0.4× 73 774
Zhenyi Chen China 16 403 0.9× 614 2.3× 199 0.8× 94 0.4× 437 3.5× 78 994

Countries citing papers authored by Yaochen Xie

Since Specialization
Citations

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

Fields of papers citing papers by Yaochen Xie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yaochen Xie

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

All Works

19 of 19 papers shown
1.
2.
Han, Haoyu, Yaochen Xie, Xianfeng Tang, et al.. (2025). Reasoning with Graphs: Structuring Implicit Knowledge to Enhance LLMs Reasoning. 25698–25714.
3.
Xie, Ziqian, Hao Yuan, Yaochen Xie, et al.. (2024). Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging. Communications Biology. 7(1). 414–414. 12 indexed citations
4.
Luo, Chen, Hanqing Lu, Yaochen Xie, et al.. (2024). Exploring Query Understanding for Amazon Product Search. 2343–2348.
5.
Xie, Yaochen, Yu Ding, & Shuiwang Ji. (2022). Augmented Equivariant Attention Networks for Microscopy Image Transformation. IEEE Transactions on Medical Imaging. 41(11). 3194–3206. 1 indexed citations
6.
Xu, Xinyi, Cheng Deng, Yaochen Xie, & Shuiwang Ji. (2022). Group Contrastive Self-Supervised Learning on Graphs. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(3). 1–1. 15 indexed citations
7.
Xie, Yaochen, et al.. (2022). Self-Supervised Learning of Graph Neural Networks: A Unified Review. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(2). 2412–2429. 216 indexed citations breakdown →
8.
Wang, Zhengyang, Meng Liu, Youzhi Luo, et al.. (2022). Advanced graph and sequence neural networks for molecular property prediction and drug discovery. Bioinformatics. 38(9). 2579–2586. 63 indexed citations
9.
Xie, Yaochen, et al.. (2021). Self-Supervised Learning of Graph Neural Networks: A Unified Review. arXiv (Cornell University). 15 indexed citations
10.
Wang, Zhengyang, Yaochen Xie, & Shuiwang Ji. (2021). Global voxel transformer networks for augmented microscopy. Nature Machine Intelligence. 3(2). 161–171. 27 indexed citations
11.
Xie, Yaochen, Zhengyang Wang, & Shuiwang Ji. (2020). Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising. Neural Information Processing Systems. 33. 20320–20330. 1 indexed citations
12.
Xie, Yaochen, et al.. (2020). zhengyang-wang/GVTNets: Code for "Global Voxel Transformer Networks for Augmented Microscopy". Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
13.
Li, Xiang‐Yang, et al.. (2019). Finding the Stars in the Fireworks: Deep Understanding of Motion Sensor Fingerprint. IEEE/ACM Transactions on Networking. 27(5). 1945–1958. 11 indexed citations
14.
Li, Xiang‐Yang, et al.. (2018). Finding the Stars in the Fireworks: Deep Understanding of Motion Sensor Fingerprint. 126–134. 6 indexed citations
15.
Song, Congbo, Lin Wu, Yaochen Xie, et al.. (2017). Air pollution in China: Status and spatiotemporal variations. Environmental Pollution. 227. 334–347. 538 indexed citations breakdown →
16.
He, Jianjun, Ye Yu, Yaochen Xie, et al.. (2016). Numerical Model-Based Artificial Neural Network Model and Its Application for Quantifying Impact Factors of Urban Air Quality. Water Air & Soil Pollution. 227(7). 55 indexed citations
17.
Xie, Yaochen. (2008). Hemingway’s Language Style and Writing Techniques in The Old Man and the Sea. English Language Teaching. 1(2). 3 indexed citations
18.
Xie, Yaochen & C.N. Georghiades. (2006). Some results on the sum-rate capacity of MIMO fading broadcast channels. IEEE Transactions on Wireless Communications. 5(2). 377–383. 7 indexed citations
19.
Xie, Yaochen & C.N. Georghiades. (2005). Some results on the linear prediction of bandlimited fading processes. 1. 204–207. 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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