Pengfei Wei

927 citations
50 papers · 490 indexed · h-index 12
Topics
Domain Adaptation and Few-Shot Learning (17 papers)Geochemistry and Geologic Mapping (8 papers)Gaussian Processes and Bayesian Inference (8 papers)
Partner nations
ChinaSingaporeAustralia

In The Last Decade

Pengfei Wei

45 papers receiving 470 citations

Peers

Pengfei Wei
Comparison fields: 5 of 98
  • Artificial Intelligence 347
  • Computer Vision and Pattern Recognition 114
  • Information Systems 36
  • Control and Systems Engineering 25
  • Geophysics 25
Replace Yufeng Chen with:
Yufeng Chen China
Zhao Li China
Subhodeep Moitra United States
Yin Zhu Hong Kong
Zhongyuan Zhao China
N. Veeranjaneyulu India
Daniele Grattarola Switzerland
Langming Liu China
Anand Madhavan India
Pengfei Wei relative to Yufeng Chen China Yufeng Chen's profile →
Citations per field
00.5×4.2×
Yufeng Chen · 1×
Citations per year

Countries citing papers authored by Pengfei Wei

Since Specialization
Citations

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

Fields of papers citing papers by Pengfei Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengfei Wei

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 7
3 0
4 1
5 12
6 0
7 4
8 11
9 19
10 1
11 19
12 5
13 3
14 2
15 1
16
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler.
2
17 14
18 1
19
Deep nonlinear feature coding for unsupervised domain adaptation
33
20 7

About Pengfei Wei

Pengfei Wei is a scholar working on Computational Mathematics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 50 papers that have together received 490 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (17 papers), Geochemistry and Geologic Mapping (8 papers) and Gaussian Processes and Bayesian Inference (8 papers). The work is most often cited by research in Artificial Intelligence (347 citations), Computer Vision and Pattern Recognition (114 citations) and Signal Processing (23 citations). Pengfei Wei has collaborated with scholars based in China, Singapore and Australia. Frequent co-authors include Yiping Ke, Chi-Keong Goh, Wenxiong Liao, Bi Zeng, Yew-Soon Ong, Xinghua Qu, Fei Wu, Yimu Ji, Xiao‐Yuan Jing and Ramón Sagarna. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Expert Systems with Applications and Information Sciences.

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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