Chengxuan Ying

525 citations
2 papers · 248 indexed · 1 hit paper · h-index 1
Topics
Advanced Image and Video Retrieval Techniques (1 paper)Advanced Graph Neural Networks (1 paper)Domain Adaptation and Few-Shot Learning (1 paper)
Journals
Applied Soft ComputingNeural Information Processing Systems
Partner nations
ChinaUnited States

In The Last Decade

Chengxuan Ying

1 paper receiving 243 citations

Hit Papers

Do Transformers Really Perform Badly for Graph Representa...2021202620222024202150100150200

Peers

Chengxuan Ying
Comparison fields: 5 of 62
  • Artificial Intelligence 143
  • Computer Vision and Pattern Recognition 65
  • Molecular Biology 51
  • Computational Theory and Mathematics 46
  • Materials Chemistry 39
Replace Tianle Cai with:
Tianle Cai China
Chunjie Wang China
Ziyue Huang China
Lingfan Yu China
Yiyang Gu China
Jinjing Zhou China
Song Bian China
Cheng Ji China
Farzin Yaghmaee Iran
Chengxuan Ying relative to Tianle Cai China Tianle Cai's profile →
Citations per field
00.5×1.5×
Tianle Cai · 1×
Citations per year

Countries citing papers authored by Chengxuan Ying

Since Specialization
Citations

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

Fields of papers citing papers by Chengxuan Ying

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chengxuan Ying

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

All Works

2 of 2 papers shown
#WorkIndexed citations
1 0
2
Do Transformers Really Perform Badly for Graph Representationbreakdown →
248

About Chengxuan Ying

Chengxuan Ying is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Infectious Diseases, having authored 2 papers that have together received 248 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (1 paper), Advanced Graph Neural Networks (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). The work is most often cited by research in Artificial Intelligence (143 citations), Computer Vision and Pattern Recognition (65 citations) and Computational Theory and Mathematics (46 citations). Chengxuan Ying has collaborated with scholars based in China and United States. Frequent co-authors include Tianle Cai, Guolin Ke, Yanming Shen, Tie‐Yan Liu, Shuxin Zheng, Di He, Shengjie Luo, Bo Xu, Yuan Lin and Hongfei Lin. Their work appears in journals such as Applied Soft Computing and Neural Information Processing Systems.

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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