Fan-Keng Sun

1.2k citations
10 papers · 733 · 1 hit paper · h-index 8

Impact in

Papers in

Fan-Keng Sun

10 papers receiving 717 citations

Fan-Keng Sun's Hit Papers

Temporal pattern attention for multivariate time series forecasting 2019 · 630 citations
6300+2+4Years since publication200400600

Peers

Fan-Keng Sun
Comparison fields: 5 of 93
  • Signal Processing 202
  • Management Science and Operations Research 200
  • Building and Construction 140
  • Artificial Intelligence 248
  • Transportation 43
Replace Muxi Chen with:
Muxi Chen Hong Kong
Yuxiu Hua China
Ziqing Ma China
Ella Pereira United Kingdom
Abdelouhab Zeroual Morocco
Abderrazak Sebaa Algeria
Mahdi Khodayar United States
Chengqing Yu China
Jian Guo China
Fan-Keng Sun relative to Muxi Chen Hong Kong Muxi Chen's profile →
Citations per field
00.5×1.5×
Muxi Chen · 1×
Citations per year

Countries citing papers authored by Fan-Keng Sun

Since Specialization
Citations

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

Fields of papers citing papers by Fan-Keng Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fan-Keng Sun. 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 Fan-Keng Sun. The network helps show where Fan-Keng Sun may publish in the future.

Co-authors

The 9 scholars most cited alongside Fan-Keng Sun, 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 Fan-Keng Sun Line = papers co-authored together Fan-Keng Sun links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1
Temporal pattern attention for multivariate time series forecasting
Hit paper breakdown →
2019630
2 201823
3 202220
4
LAMOL: LAnguage MOdeling for Lifelong Language Learning
201915
5 202014
6
LAMAL: LAnguage Modeling Is All You Need for Lifelong Language Learning
20198
7 20198
8 20197
9 20224
10 20214

About Fan-Keng Sun

Fan-Keng Sun is a scholar working on Artificial Intelligence, Hardware and Architecture, Electrical and Electronic Engineering, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 10 papers that have together received 733 indexed citations. Recurring topics across this work include VLSI and FPGA Design Techniques (4 papers), VLSI and Analog Circuit Testing (3 papers), Data Stream Mining Techniques (2 papers), Multimodal Machine Learning Applications (2 papers), Interconnection Networks and Systems (2 papers), Topic Modeling (2 papers), Time Series Analysis and Forecasting (1 paper) and Advanced Statistical Process Monitoring (1 paper). The work is most often cited by research in Signal Processing (202 citations), Management Science and Operations Research (200 citations), Building and Construction (140 citations), Artificial Intelligence (248 citations) and Transportation (43 citations). Fan-Keng Sun has collaborated with scholars based in Taiwan and United States. Frequent co-authors include Hung-yi Lee, Yao‐Wen Chang, Ching‐Yu Chen, Hao Chen, Hao Chen, Duane S. Boning, John T. Ruth, Kyongmin Yeo and Jayant Kalagnanam. Their work appears in journals such as IEEE Transactions on Semiconductor Manufacturing, SIAM Journal on Scientific Computing, Machine Learning, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems and arXiv (Cornell University).

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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