Nate Strawn
Impact in
- Statistics and Probability top 10%
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
Papers in
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- Mathematical Analysis and Transform Methods 6
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- Statistical Methods and Inference 5
- Co-authors
- David B. Dunson (3 shared papers)Dustin G. Mixon (3 shared papers)Jameson Cahill (3 shared papers)A. Armağan (2 shared papers)Jong‐Koo Lee (1 shared paper)Waheed U. Bajwa (1 shared paper)Hongxiao Zhu (1 shared paper)Matthew C. Fickus (1 shared paper)
- Journals
- Information and Inference A Journal of the IMA (1 paper)SIAM Journal on Applied Algebra and Geometry (1 paper)IEEE Transactions on Aerospace and Electronic Systems (1 paper)Cytokine (1 paper)Advances in Computational Mathematics (1 paper)
- Partner nations
- United StatesSouth Korea
In The Last Decade
Nate Strawn
15 papers receiving 141 citations
Peers
Comparison fields: 5 of 60
- Computational Mathematics 5
- Statistics and Probability 42
- Applied Mathematics 49
- Acoustics and Ultrasonics 2
- Computational Mechanics 32
Countries citing papers authored by Nate Strawn
This map shows the geographic impact of Nate Strawn'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 Nate Strawn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nate Strawn more than expected).
Fields of papers citing papers by Nate Strawn
This network shows the impact of papers produced by Nate Strawn. 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 Nate Strawn. The network helps show where Nate Strawn may publish in the future.
Co-authors
The 22 scholars most cited alongside Nate Strawn, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 35 | |
| 2 | 2017 | 20 | |
| 3 | 2013 | 16 | |
| 4 | 2010 | 16 | |
| 5 | Journal of Machine Learning Research | 2016 | 14 |
| 6 | 2015 | 12 | |
| 7 | 2011 | 9 | |
| 8 | 2012 | 7 | |
| 9 | 2016 | 4 | |
| 10 | 2014 | 3 | |
| 11 | 2011 | 3 | |
| 12 | 2019 | 3 | |
| 13 | 2014 | 3 | |
| 14 | 2024 | 2 | |
| 15 | 2015 | 1 | |
| 16 | 2015 | 0 |
About Nate Strawn
Nate Strawn is a scholar working on Applied Mathematics, Statistics and Probability, Computational Mechanics, Computational Theory and Mathematics and Statistical and Nonlinear Physics, having authored 16 papers that have together received 148 indexed citations. Recurring topics across this work include Mathematical Analysis and Transform Methods (6 papers), Statistical Methods and Inference (5 papers), Sparse and Compressive Sensing Techniques (4 papers), Seismic Imaging and Inversion Techniques (3 papers), Topological and Geometric Data Analysis (3 papers), Nonlinear Waves and Solitons (3 papers), Advanced Numerical Analysis Techniques (2 papers) and Bayesian Methods and Mixture Models (2 papers). The work is most often cited by research in Computational Mathematics (5 citations), Statistics and Probability (42 citations), Applied Mathematics (49 citations), Acoustics and Ultrasonics (2 citations) and Computational Mechanics (32 citations). Nate Strawn has collaborated with scholars based in United States and South Korea. Frequent co-authors include David B. Dunson, Dustin G. Mixon, Jameson Cahill, A. Armağan, Jong‐Koo Lee, Waheed U. Bajwa, Hongxiao Zhu, Matthew C. Fickus, Stanislav Minsker and Igor Griva. Their work appears in journals such as Information and Inference A Journal of the IMA, SIAM Journal on Applied Algebra and Geometry, IEEE Transactions on Aerospace and Electronic Systems, Cytokine and Advances in Computational Mathematics.
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.