Heng Lian

2.9k total citations
222 papers, 1.9k citations indexed

About

Heng Lian is a scholar working on Statistics and Probability, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Heng Lian has authored 222 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 184 papers in Statistics and Probability, 71 papers in Artificial Intelligence and 42 papers in Computational Mechanics. Recurrent topics in Heng Lian's work include Statistical Methods and Inference (177 papers), Statistical Methods and Bayesian Inference (68 papers) and Advanced Statistical Methods and Models (58 papers). Heng Lian is often cited by papers focused on Statistical Methods and Inference (177 papers), Statistical Methods and Bayesian Inference (68 papers) and Advanced Statistical Methods and Models (58 papers). Heng Lian collaborates with scholars based in China, Hong Kong and Singapore. Heng Lian's co-authors include Gaorong Li, Peng Lai, Robert B. Gramacy, Hua Liang, Weihua Zhao, Maozai Tian, Youxi Luo, Liugen Xue, Li‐Chun Wang and Lei Wang and has published in prestigious journals such as Journal of the American Statistical Association, Bioinformatics and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Heng Lian

202 papers receiving 1.8k citations

Peers

Heng Lian
Comparison fields: 5 of 115
  • Statistics and Probability 1.3k
  • Artificial Intelligence 578
  • Control and Systems Engineering 250
  • Computer Vision and Pattern Recognition 158
  • Computational Mechanics 157
Replace Chenlei Leng with:
Chenlei Leng Singapore
Lixing Zhu China
Pascal Sarda France
Marten Wegkamp United States
Harro Walk Germany
Sam Efromovich United States
Holger Höfling United States
Qin Jin China
Chenlei Leng Singapore View profile →
Citations per field, relative to Heng Lian
Heng Lian · 1×
Citations per year, relative to Heng Lian
Heng Lian · 1×

Countries citing papers authored by Heng Lian

Since Specialization
Citations

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

Fields of papers citing papers by Heng Lian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heng Lian

This figure shows the co-authorship network connecting the top 25 collaborators of Heng Lian. A scholar is included among the top collaborators of Heng Lian 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 Heng Lian. Heng Lian 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 2
2 2
3 1
4 0
5 3
6 0
7 1
8 2
9 1
10 1
11 4
12 2
13
High-dimensional quantile tensor regression
14
14 4
15 3
16
Divide-and-conquer for debiased l 1 -norm support vector machine in ultra-high dimensions
26
17
A debiased distributed estimation for sparse partially linear models in diverging dimensions
4
18 35
19 64
20
Functional Partial Linear Regression
3

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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