Yaochen Xie

1.6k citations
19 papers · 972 · 2 hit papers · h-index 9

Impact in

Papers in

Yaochen Xie

16 papers receiving 961 citations

Hit Papers

Self-Supervised Learning of Graph Neural Networks: A Unified Review 2022 · 216 citations
2160+3+6Years since publication100200300400500

Peers

Yaochen Xie
Comparison fields: 5 of 115
  • Health, Toxicology and Mutagenesis 449
  • Environmental Engineering 251
  • Atmospheric Science 266
  • Automotive Engineering 82
  • Artificial Intelligence 212
Replace Da Gao with:
Da Gao China
Zhenyi Chen China
Shaofu Lin China
Giorgio Corani Switzerland
Pengfei Li China
Xianneng Li China
Jiwu Jing China
Liqun Liu China
Jin Fan China
Chia‐Li Chen Taiwan
Yaochen Xie relative to Da Gao China Da Gao's profile →
Citations per field
00.5×3.8×
Da Gao · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Yaochen Xie, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yaochen Xie Line = papers co-authored together Yaochen Xie links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1
Air pollution in China: Status and spatiotemporal variations
Hit paper breakdown →
2017538
2
Self-Supervised Learning of Graph Neural Networks: A Unified Review
Hit paper breakdown →
2022216
3 202263
4 201655
5 202127
6 202115
7 202215
8 202412
9 201911
10 20067
11 20186
12 20083
13
Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising
20201
14 20221
15 20051
16 20201
17 20250
18 20240
19 20250

About Yaochen Xie

Yaochen Xie is a scholar working on Artificial Intelligence, Information Systems, Media Technology, Computer Vision and Pattern Recognition and Biophysics, having authored 19 papers that have together received 972 indexed citations. Recurring topics across this work include Image Processing Techniques and Applications (4 papers), Cell Image Analysis Techniques (3 papers), Text and Document Classification Technologies (3 papers), Advanced Graph Neural Networks (3 papers), Topic Modeling (3 papers), Advanced Wireless Network Optimization (2 papers), Advanced Fluorescence Microscopy Techniques (2 papers) and Atmospheric chemistry and aerosols (2 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (449 citations), Environmental Engineering (251 citations), Atmospheric Science (266 citations), Automotive Engineering (82 citations) and Artificial Intelligence (212 citations). Yaochen Xie has collaborated with scholars based in United States and China. Frequent co-authors include Shuiwang Ji, Zhengyang Wang, Xu Zhao, Jianjun He, Lin Wu, Hongjun Mao, Xi Chen, Liu Yan, Qili Dai and Yingchao Lin. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Medical Imaging, Water Air & Soil Pollution, IEEE Transactions on Wireless Communications and Communications Biology.

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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