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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- Machine Learning and Algorithms 6
- Domain Adaptation and Few-Shot Learning 4
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- Advanced Image Processing Techniques 3
- Co-authors
- Alfred O. Hero (5 shared papers)Nicolás García Trillos (2 shared papers)Anthony Yezzi (3 shared papers)A.-R. Mansouri (3 shared papers)Rachid Deriche (1 shared paper)Maxime Descoteaux (1 shared paper)Selim Esedoḡlu (4 shared papers)Ko-Jen Hsiao (2 shared papers)
- Journals
- SIAM Journal on Mathematical Analysis (4 papers)Applied and Computational Harmonic Analysis (2 papers)Journal of Mathematical Imaging and Vision (2 papers)SIAM Journal on Imaging Sciences (2 papers)Transactions of the American Mathematical Society (2 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Jeff Calder
40 papers receiving 408 citations
Peers
Comparison fields: 5 of 81
- Statistics and Probability 62
- Mathematical Physics 56
- Computer Vision and Pattern Recognition 127
- Computational Theory and Mathematics 98
- Geometry and Topology 37
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 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1971 | 37 | |
| 2 | 2009 | 35 | |
| 3 | 2018 | 32 | |
| 4 | 2010 | 31 | |
| 5 | 2022 | 26 | |
| 6 | 2018 | 18 | |
| 7 | 2021 | 17 | |
| 8 | 2022 | 15 | |
| 9 | 2022 | 15 | |
| 10 | 2020 | 15 | |
| 11 | 2015 | 15 | |
| 12 | 1Pareto-depth for Multiple-query Image Retrieval | 2016 | 14 |
| 13 | 2014 | 14 | |
| 14 | 2011 | 14 | |
| 15 | Lipschitz regularized Deep Neural Networks converge and generalize | 2018 | 13 |
| 16 | 1973 | 13 | |
| 17 | 2022 | 12 | |
| 18 | 2020 | 12 | |
| 19 | 2021 | 11 | |
| 20 | 2022 | 11 |
About Jeff Calder
Jeff Calder is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Statistics and Probability, Mathematical Physics and Computational Theory and Mathematics, having authored 46 papers that have together received 453 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), Point processes and geometric inequalities (3 papers), Markov Chains and Monte Carlo Methods (3 papers), Numerical methods in inverse problems (3 papers), Advanced Image Processing Techniques (3 papers) and Optimization and Variational Analysis (3 papers). The work is most often cited by research in Statistics and Probability (62 citations), Mathematical Physics (56 citations), Computer Vision and Pattern Recognition (127 citations), Computational Theory and Mathematics (98 citations) and Geometry and Topology (37 citations). Jeff Calder has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Alfred O. Hero, Nicolás García Trillos, Anthony Yezzi, A.-R. Mansouri, Rachid Deriche, Maxime Descoteaux, Selim Esedoḡlu, Ko-Jen Hsiao, Dejan Slepčev and Adam M. Oberman. Their work appears in journals such as SIAM Journal on Mathematical Analysis, Applied and Computational Harmonic Analysis, Journal of Mathematical Imaging and Vision, SIAM Journal on Imaging Sciences and Transactions of the American Mathematical Society.
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.