Zihao Ye

34 papers receiving 798 citations

Peers

Zihao Ye
Comparison fields: 5 of 117
  • Computational Mathematics 24
  • Hardware and Architecture 89
  • Artificial Intelligence 403
  • Computer Vision and Pattern Recognition 235
  • Computer Networks and Communications 116
Replace Feng Yan with:
Feng Yan United States
Pedro Ribeiro Portugal
Bill G. Horne United States
Zhen Ling China
Xingang Liu China
Lixin Han China
Ji Li China
Masahito Kurihara Japan
Zihao Ye relative to Feng Yan United States Feng Yan's profile →
Citations per field
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Citations per year

Countries citing papers authored by Zihao Ye

Since Specialization
Citations

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

Fields of papers citing papers by Zihao Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Zihao Ye, 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 Zihao Ye Line = papers co-authored together Zihao Ye links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs
2019273
2 202091
3 202186
4 201869
5 202353
6 202044
7 202339
8 201222
9 202316
10 201714
11 202113
12 202312
13 202310
14 20129
15 20237
16 20237
17 20217
18 20246
19 20205
20 20214

About Zihao Ye

Zihao Ye is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Ecology, Global and Planetary Change and Nature and Landscape Conservation, having authored 41 papers that have together received 815 indexed citations. Recurring topics across this work include Turtle Biology and Conservation (5 papers), Amphibian and Reptile Biology (5 papers), Soil Carbon and Nitrogen Dynamics (4 papers), Aquaculture Nutrition and Growth (3 papers), Topic Modeling (3 papers), Graph Theory and Algorithms (3 papers), Advanced Graph Neural Networks (3 papers) and Parallel Computing and Optimization Techniques (3 papers). The work is most often cited by research in Computational Mathematics (24 citations), Hardware and Architecture (89 citations), Artificial Intelligence (403 citations), Computer Vision and Pattern Recognition (235 citations) and Computer Networks and Communications (116 citations). Zihao Ye has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Da Zheng, Chao Ma, Zheng Zhang, Minjie Wang, Llewellyn Tang, Mufei Li, Alexander J. Smola, Quan Gan, Qi Huang and Jinjing Zhou. Their work appears in journals such as Chelonian Conservation and Biology, Agriculture Ecosystems & Environment, Global Ecology and Conservation, Construction Innovation and Agronomy.

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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