Weiyi Liu

885 total citations
66 papers, 550 citations indexed

About

Weiyi Liu is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Computational Theory and Mathematics. According to data from OpenAlex, Weiyi Liu has authored 66 papers receiving a total of 550 indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Artificial Intelligence, 18 papers in Statistical and Nonlinear Physics and 18 papers in Computational Theory and Mathematics. Recurrent topics in Weiyi Liu's work include Bayesian Modeling and Causal Inference (23 papers), Complex Network Analysis Techniques (17 papers) and Rough Sets and Fuzzy Logic (17 papers). Weiyi Liu is often cited by papers focused on Bayesian Modeling and Causal Inference (23 papers), Complex Network Analysis Techniques (17 papers) and Rough Sets and Fuzzy Logic (17 papers). Weiyi Liu collaborates with scholars based in China, United States and Taiwan. Weiyi Liu's co-authors include Kun Yue, Toyotaro Suzumura, Pin‐Yu Chen, Guangmin Hu, Guoguang Mu, Zhaoqi Wang, Inseok Hwang, Xiaoling Wang, Jin Li and Jin Li and has published in prestigious journals such as PLoS ONE, Scientific Reports and Expert Systems with Applications.

In The Last Decade

Weiyi Liu

62 papers receiving 526 citations

Peers

Weiyi Liu
Comparison fields: 5 of 81
  • Artificial Intelligence 275
  • Statistical and Nonlinear Physics 161
  • Computer Networks and Communications 111
  • Computer Vision and Pattern Recognition 98
  • Information Systems 96
Replace Zengfeng Huang with:
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Qi Cao China
Doo-Soon Park South Korea
Bilian Chen China
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Zengfeng Huang China View profile →
Citations per field, relative to Weiyi Liu
Weiyi Liu · 1×
Citations per year, relative to Weiyi Liu
Weiyi Liu · 1×

Countries citing papers authored by Weiyi Liu

Since Specialization
Citations

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

Fields of papers citing papers by Weiyi Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weiyi Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Weiyi Liu. A scholar is included among the top collaborators of Weiyi Liu 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 Weiyi Liu. Weiyi Liu 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
# Work Indexed citations
1 1
2 10
3 4
4 15
5 24
6 14
7 7
8 10
9 2
10 3
11 14
12 6
13
Qualitative representation and fusion of probabilistic causalities in time-series environments
2
14
RCC Topological Relations between Vague Regions Based on Rough Sets
2
15 8
16
State prediction based on the dynamic Bayesian network
1
17
Application of structural EM algorithm to learning Bayesian networks for small sample
1
18
An approach to learning Bayesian networks from small data set
0
19 50
20
An Object-Oriented System for the Reuse of Software Design Items.
1

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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