Yingyan Lin

78 papers receiving 1.1k citations

Peers

Yingyan Lin
Comparison fields: 5 of 71
  • Computer Vision and Pattern Recognition 535
  • Hardware and Architecture 148
  • Computer Graphics and Computer-Aided Design 72
  • Artificial Intelligence 489
  • Computer Networks and Communications 192
Replace Yuzhe Ma with:
Yuzhe Ma Hong Kong
Xingyu Liu China
Li Jiang China
Yuandong Tian United States
Jaewoong Sim United States
Eunhyeok Park South Korea
Paul N. Whatmough United States
Bhargab B. Bhattacharya India
Susmita Sur‐Kolay India
Cihang Xie United States
Yingyan Lin relative to Yuzhe Ma Hong Kong Yuzhe Ma's profile →
Citations per field
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Yuzhe Ma · 1×
Citations per year

Countries citing papers authored by Yingyan Lin

Since Specialization
Citations

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

Fields of papers citing papers by Yingyan Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018156
2 202197
3 202364
4 202356
5 202051
6 202345
7 202244
8 201735
9 202034
10 202334
11 202231
12 202331
13 202030
14
Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks
202027
15 202026
16 202025
17 202425
18 202025
19 202322
20 202419

About Yingyan Lin

Yingyan Lin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Hardware and Architecture and Computational Mechanics, having authored 85 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (28 papers), Advanced Memory and Neural Computing (16 papers), Adversarial Robustness in Machine Learning (14 papers), Domain Adaptation and Few-Shot Learning (11 papers), Ferroelectric and Negative Capacitance Devices (10 papers), Computer Graphics and Visualization Techniques (9 papers), 3D Shape Modeling and Analysis (8 papers) and Parallel Computing and Optimization Techniques (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (535 citations), Hardware and Architecture (148 citations), Computer Graphics and Computer-Aided Design (72 citations), Artificial Intelligence (489 citations) and Computer Networks and Communications (192 citations). Yingyan Lin has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Chaojian Li, Haoran You, Yongan Zhang, Yang Zhao, Yonggan Fu, Zimu Zhou, Junzhao Du, Sicong Liu, Hui Liu and Zhongzhi Yu. Their work appears in journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on Circuits and Systems I Regular Papers, IEEE Micro, IEEE Journal of Selected Topics in Signal Processing and ACM Journal on Emerging Technologies in Computing 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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