Jeff Calder
Impact in
- Statistics and Probability top 5%
- Statistical Methods and Inference
- Mathematical Physics top 10%
- Numerical methods in inverse problems
Papers in
-
- Machine Learning and Algorithms 6
- Domain Adaptation and Few-Shot Learning 4
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- Statistical Methods and Inference 6
- Markov Chains and Monte Carlo Methods 3
- Co-authors
- Anthony Yezzi (3 shared papers)A.-R. Mansouri (3 shared papers)Nicolás García Trillos (2 shared papers)Alfred O. Hero (4 shared papers)Rachid Deriche (1 shared paper)Maxime Descoteaux (1 shared paper)Selim Esedoḡlu (4 shared papers)Dejan Slepčev (3 shared papers)
- Journals
- SIAM Journal on Mathematical Analysis (4 papers)Journal of Mathematical Imaging and Vision (2 papers)Transactions of the American Mathematical Society (2 papers)Medical Image Analysis (2 papers)SIAM Journal on Imaging Sciences (2 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Jeff Calder
35 papers receiving 333 citations
Peers
Comparison fields: 5 of 74
- Statistics and Probability 61
- Mathematical Physics 52
- Computational Theory and Mathematics 90
- Computer Vision and Pattern Recognition 106
- Geometry and Topology 35
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 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 30 | |
| 2 | 1971 | 30 | |
| 3 | 2010 | 29 | |
| 4 | 2018 | 27 | |
| 5 | 2022 | 21 | |
| 6 | 2021 | 17 | |
| 7 | 2018 | 16 | |
| 8 | 2020 | 15 | |
| 9 | 2022 | 14 | |
| 10 | Lipschitz regularized Deep Neural Networks converge and generalize | 2018 | 13 |
| 11 | 2014 | 13 | |
| 12 | 2011 | 13 | |
| 13 | 2015 | 12 | |
| 14 | 1973 | 12 | |
| 15 | 2020 | 12 | |
| 16 | 2022 | 10 | |
| 17 | 2022 | 10 | |
| 18 | 2019 | 9 | |
| 19 | 2021 | 9 | |
| 20 | 1970 | 8 |
About Jeff Calder
Jeff Calder is a scholar working on Artificial Intelligence, Statistics and Probability, Computer Vision and Pattern Recognition, Mathematical Physics and Computational Theory and Mathematics, having authored 41 papers that have together received 374 indexed citations. Recurring topics across this work include Statistical Methods and Inference (6 papers), Machine Learning and Algorithms (6 papers), Domain Adaptation and Few-Shot Learning (4 papers), Numerical methods in inverse problems (3 papers), Advanced Numerical Analysis Techniques (3 papers), Point processes and geometric inequalities (3 papers), Medical Imaging Techniques and Applications (3 papers) and Markov Chains and Monte Carlo Methods (3 papers). The work is most often cited by research in Statistics and Probability (61 citations), Mathematical Physics (52 citations), Computational Theory and Mathematics (90 citations), Computer Vision and Pattern Recognition (106 citations) and Geometry and Topology (35 citations). Jeff Calder has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Anthony Yezzi, A.-R. Mansouri, Nicolás García Trillos, Alfred O. Hero, Rachid Deriche, Maxime Descoteaux, Selim Esedoḡlu, Dejan Slepčev, Adam M. Oberman and Charles K. Smart. Their work appears in journals such as SIAM Journal on Mathematical Analysis, Journal of Mathematical Imaging and Vision, Transactions of the American Mathematical Society, Medical Image Analysis and SIAM Journal on Imaging Sciences.
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.