Jeff Calder
Impact in
- Statistics and Probability top 5%
- Statistical Methods and Inference
- Mathematical Physics top 10%
- Numerical methods in inverse problems
Papers in
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- Statistical Methods and Inference 7
- Markov Chains and Monte Carlo Methods 4
- Co-authors
- Nicolás García Trillos (2 shared papers)A.-R. Mansouri (3 shared papers)Anthony Joseph Yezzi (3 shared papers)Rachid Deriche (1 shared paper)Alfred O. Hero (4 shared papers)Maxime Descoteaux (1 shared paper)Dejan Slepčev (4 shared papers)Selim Esedoḡlu (4 shared papers)
- Journals
- SIAM Journal on Mathematical Analysis (4 papers)Medical Image Analysis (2 papers)Journal of Mathematical Imaging and Vision (2 papers)SIAM Journal on Imaging Sciences (2 papers)Applied and Computational Harmonic Analysis (2 papers)
- Partner nations
- United StatesCanadaKazakhstan
In The Last Decade
Jeff Calder
42 papers receiving 416 citations
Peers
Comparison fields: 5 of 77
- Statistics and Probability 69
- Mathematical Physics 60
- Computational Theory and Mathematics 104
- Computer Vision and Pattern Recognition 111
- Applied Mathematics 49
Countries citing papers authored by Jeff Calder
This map shows the geographic impact of Jeff Calder'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 Jeff Calder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeff Calder more than expected).
Fields of papers citing papers by Jeff Calder
This network shows the impact of papers produced by Jeff Calder. 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 Jeff Calder. The network helps show where Jeff Calder may publish in the future.
Co-authors
The 25 scholars most cited alongside Jeff Calder, 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 49 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 38 | |
| 2 | 1971 | 38 | |
| 3 | 2009 | 37 | |
| 4 | 2010 | 33 | |
| 5 | 2022 | 28 | |
| 6 | 2018 | 19 | |
| 7 | 2020 | 17 | |
| 8 | 2021 | 16 | |
| 9 | 2022 | 15 | |
| 10 | 2022 | 15 | |
| 11 | 2015 | 15 | |
| 12 | 2011 | 14 | |
| 13 | 2014 | 14 | |
| 14 | 2022 | 13 | |
| 15 | 2022 | 13 | |
| 16 | 2020 | 13 | |
| 17 | 1973 | 12 | |
| 18 | 2021 | 11 | |
| 19 | 2022 | 10 | |
| 20 | 2019 | 9 |
About Jeff Calder
Jeff Calder is a scholar working on Statistics and Probability, Mathematical Physics, Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 49 papers that have together received 460 indexed citations. Recurring topics across this work include Statistical Methods and Inference (7 papers), Domain Adaptation and Few-Shot Learning (6 papers), Machine Learning and Algorithms (6 papers), Markov Chains and Monte Carlo Methods (4 papers), Advanced SAR Imaging Techniques (3 papers), Forensic Anthropology and Bioarchaeology Studies (3 papers), Image and Signal Denoising Methods (3 papers) and Advanced Image Processing Techniques (3 papers). The work is most often cited by research in Statistics and Probability (69 citations), Mathematical Physics (60 citations), Computational Theory and Mathematics (104 citations), Computer Vision and Pattern Recognition (111 citations) and Applied Mathematics (49 citations). Jeff Calder has collaborated with scholars based in United States, Canada and Kazakhstan. Frequent co-authors include Nicolás García Trillos, A.-R. Mansouri, Anthony Joseph Yezzi, Rachid Deriche, Alfred O. Hero, Maxime Descoteaux, Dejan Slepčev, Selim Esedoḡlu, Charles K. Smart and Matthew Thorpe. Their work appears in journals such as SIAM Journal on Mathematical Analysis, Medical Image Analysis, Journal of Mathematical Imaging and Vision, SIAM Journal on Imaging Sciences and Applied and Computational Harmonic Analysis.
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.