Weichen Wang

1.1k citations
25 papers · 596 · h-index 10

Impact in

Papers in

Weichen Wang

22 papers receiving 582 citations

Peers

Weichen Wang
Comparison fields: 5 of 86
  • Statistics and Probability 201
  • Computational Mathematics 10
  • Finance 99
  • General Economics, Econometrics and Finance 35
  • Signal Processing 40
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Beatrix Jones New Zealand
Veronika Ročková United States
Ker-Chau Li United States
Hrvoje Šikić Croatia
Changyi Park South Korea
Jorge M. Arevalillo Spain
Ryan Gill United States
Matthias Kirchner Germany
Grace S. Shieh Taiwan
Enrico Capobianco United States
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Citations per field
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Citations per year

Countries citing papers authored by Weichen Wang

Since Specialization
Citations

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

Fields of papers citing papers by Weichen Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017103
2 202284
3
Projected Principal Component Analysis in Factor Models
201680
4 201559
5 201849
6 201248
7 201845
8 202144
9
An l Eigenvector Perturbation Bound and Its Application to Robust Covariance Estimation.
201814
10 202112
11
Estimation of Functionals of Sparse Covariance Matrices
20168
12 20258
13
[Two novel EIF2AK3 mutations in a Chinese boy with Wolcott-Rallison syndrome].
20117
14 20226
15 20186
16 20245
17 20145
18 20115
19 20243
20 20222

About Weichen Wang

Weichen Wang is a scholar working on Statistics and Probability, Molecular Biology, Artificial Intelligence, Pulmonary and Respiratory Medicine and Signal Processing, having authored 25 papers that have together received 596 indexed citations. Recurring topics across this work include Statistical Methods and Inference (8 papers), Advanced Statistical Methods and Models (5 papers), Statistical Methods and Bayesian Inference (4 papers), Ferroptosis and cancer prognosis (2 papers), Blind Source Separation Techniques (2 papers), Sparse and Compressive Sensing Techniques (2 papers), Neural Networks and Applications (2 papers) and Random Matrices and Applications (2 papers). The work is most often cited by research in Statistics and Probability (201 citations), Computational Mathematics (10 citations), Finance (99 citations), General Economics, Econometrics and Finance (35 citations) and Signal Processing (40 citations). Weichen Wang has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Jianqing Fan, Yuan Liao, Yiqiao Zhong, Han Liu, Ziwei Zhu, Xuegong Zhang, Bing Wu, Maoyu Wang, Peipei Gong and Zhixing Feng. Their work appears in journals such as The Annals of Statistics, Journal of Econometrics, Frontiers in Pharmacology, Frontiers in Immunology and Chinese Journal of Chemistry.

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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