Shiwei Lan
Impact in
- Statistics and Probability top 5%
- Markov Chains and Monte Carlo Methods
- Statistical Methods and Inference
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- Probabilistic and Robust Engineering Design
Papers in
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- Gaussian Processes and Bayesian Inference 13
- Bayesian Methods and Mixture Models 9
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- Markov Chains and Monte Carlo Methods 11
- Statistical Methods and Inference 3
- Co-authors
- Babak Shahbaba (11 shared papers)Mark Girolami (5 shared papers)Andrew M. Stuart (2 shared papers)Alexandros Beskos (1 shared paper)Patrick E. Farrell (1 shared paper)Alfredo Garbuno-Iñigo (1 shared paper)Tapio Schneider (1 shared paper)Vladimir N. Minin (2 shared papers)
- Journals
- Journal of Computational Physics (4 papers)Statistics and Computing (2 papers)Bioinformatics (1 paper)Journal of the American Statistical Association (1 paper)Journal of Computational and Graphical Statistics (1 paper)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Shiwei Lan
21 papers receiving 357 citations
Peers
Comparison fields: 5 of 88
- Statistics and Probability 118
- Statistics, Probability and Uncertainty 69
- Artificial Intelligence 149
- Statistical and Nonlinear Physics 48
- Modeling and Simulation 15
Countries citing papers authored by Shiwei Lan
This map shows the geographic impact of Shiwei Lan'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 Shiwei Lan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shiwei Lan more than expected).
Fields of papers citing papers by Shiwei Lan
This network shows the impact of papers produced by Shiwei Lan. 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 Shiwei Lan. The network helps show where Shiwei Lan may publish in the future.
Co-authors
The 25 scholars most cited alongside Shiwei Lan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 73 | |
| 2 | 2020 | 67 | |
| 3 | 2016 | 31 | |
| 4 | 2013 | 30 | |
| 5 | 2015 | 30 | |
| 6 | 2014 | 24 | |
| 7 | 2014 | 20 | |
| 8 | 2015 | 20 | |
| 9 | 2016 | 15 | |
| 10 | 2022 | 14 | |
| 11 | 2017 | 11 | |
| 12 | 2019 | 7 | |
| 13 | 2017 | 6 | |
| 14 | 2019 | 5 | |
| 15 | 2023 | 3 | |
| 16 | 2023 | 3 | |
| 17 | 2024 | 2 | |
| 18 | Nonparametric fisher geometry with application to density estimation | 2020 | 2 |
| 19 | 2012 | 2 | |
| 20 | 2019 | 1 |
About Shiwei Lan
Shiwei Lan is a scholar working on Artificial Intelligence, Statistics and Probability, Statistics, Probability and Uncertainty, Geometry and Topology and Computer Vision and Pattern Recognition, having authored 24 papers that have together received 367 indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (13 papers), Markov Chains and Monte Carlo Methods (11 papers), Bayesian Methods and Mixture Models (9 papers), Probabilistic and Robust Engineering Design (6 papers), Statistical Methods and Inference (3 papers), Morphological variations and asymmetry (3 papers), Model Reduction and Neural Networks (2 papers) and Natural Fiber Reinforced Composites (1 paper). The work is most often cited by research in Statistics and Probability (118 citations), Statistics, Probability and Uncertainty (69 citations), Artificial Intelligence (149 citations), Statistical and Nonlinear Physics (48 citations) and Modeling and Simulation (15 citations). Shiwei Lan has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Babak Shahbaba, Mark Girolami, Andrew M. Stuart, Alexandros Beskos, Patrick E. Farrell, Alfredo Garbuno-Iñigo, Tapio Schneider, Vladimir N. Minin, Julia A. Palacios and Michael D. Karcher. Their work appears in journals such as Journal of Computational Physics, Statistics and Computing, Bioinformatics, Journal of the American Statistical Association and Journal of Computational and Graphical Statistics.
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.