Mingyu Yan

32 papers receiving 611 citations

Mingyu Yan's Hit Papers

HyGCN: A GCN Accelerator with Hybrid Architecture 2020 · 222 citations
2220+2+4Years since publication50100150200

Peers

Mingyu Yan
Comparison fields: 5 of 65
  • Hardware and Architecture 109
  • Computer Vision and Pattern Recognition 330
  • Artificial Intelligence 401
  • Computational Mathematics 5
  • Computer Networks and Communications 110
Replace Jungwook Choi with:
Jungwook Choi South Korea
Tianqi Wang China
Jintao Zhang China
Youwei Zhuo China
Tong Geng United States
Yuke Wang United States
Jeng-Hau Lin United States
Darryl Dexu Lin Canada
Brian Van Essen United States
Mingyu Yan relative to Jungwook Choi South Korea Jungwook Choi's profile →
Citations per field
00.5×1.5×2.5×
Jungwook Choi · 1×
Citations per year

Countries citing papers authored by Mingyu Yan

Since Specialization
Citations

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

Fields of papers citing papers by Mingyu Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1
HyGCN: A GCN Accelerator with Hybrid Architecture
Hit paper breakdown →
2020222
2 202176
3 201967
4 202043
5 202134
6 202231
7 202323
8 202121
9 202212
10 202012
11 202210
12 202210
13 20146
14 20226
15 20215
16 20215
17 20225
18 20235
19 20234
20 20244

About Mingyu Yan

Mingyu Yan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Hardware and Architecture, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 36 papers that have together received 624 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (18 papers), Graph Theory and Algorithms (14 papers), Parallel Computing and Optimization Techniques (9 papers), Ferroelectric and Negative Capacitance Devices (6 papers), Topic Modeling (4 papers), Complex Network Analysis Techniques (4 papers), Advanced Memory and Neural Computing (3 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Hardware and Architecture (109 citations), Computer Vision and Pattern Recognition (330 citations), Artificial Intelligence (401 citations), Computational Mathematics (5 citations) and Computer Networks and Communications (110 citations). Mingyu Yan has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Dongrui Fan, Xiaochun Ye, Lei Deng, Yuan Xie, Zhimin Zhang, Xing Hu, Yujing Feng, Ling Liang, Guoqi Li and Xin Liu. Their work appears in journals such as IEEE Computer Architecture Letters, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on Parallel and Distributed Systems, IEEE Journal of Selected Topics in Signal Processing and Neural Networks.

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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