David Widemann
Impact in
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- Model Reduction and Neural Networks
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- Probabilistic and Robust Engineering Design
Papers in
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- Advanced Memory and Neural Computing 4
- Ferroelectric and Negative Capacitance Devices 4
- Co-authors
- Youngkyu Kim (1 shared paper)Tarek I. Zohdi (1 shared paper)Youngsoo Choi (1 shared paper)Adam Moody (4 shared papers)Brendt Wohlberg (1 shared paper)Youzuo Lin (1 shared paper)Felix Krahmer (1 shared paper)Tarek M. Taha (2 shared papers)
- Journals
- Journal of Biomedical Informatics (1 paper)IEEE Journal on Emerging and Selected Topics in Circuits and Systems (1 paper)PLoS ONE (1 paper)Journal of Computational Physics (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesNorway
In The Last Decade
David Widemann
10 papers receiving 226 citations
Peers
Comparison fields: 5 of 45
- Statistical and Nonlinear Physics 116
- Statistics, Probability and Uncertainty 43
- Media Technology 30
- Numerical Analysis 15
- Computer Vision and Pattern Recognition 54
Countries citing papers authored by David Widemann
This map shows the geographic impact of David Widemann'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 David Widemann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Widemann more than expected).
Fields of papers citing papers by David Widemann
This network shows the impact of papers produced by David Widemann. 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 David Widemann. The network helps show where David Widemann may publish in the future.
Co-authors
The 24 scholars most cited alongside David Widemann, 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 | 2021 | 129 | |
| 2 | Blind Image Deconvolution Motion Blur Estimation | 2006 | 48 |
| 3 | 2017 | 26 | |
| 4 | 2017 | 11 | |
| 5 | 2018 | 9 | |
| 6 | 2019 | 6 | |
| 7 | 2020 | 2 | |
| 8 | 2021 | 1 | |
| 9 | 2017 | 1 | |
| 10 | 2022 | 1 |
About David Widemann
David Widemann is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Cognitive Neuroscience and Molecular Biology, having authored 10 papers that have together received 234 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (4 papers), Ferroelectric and Negative Capacitance Devices (4 papers), Neural dynamics and brain function (2 papers), Phase Equilibria and Thermodynamics (1 paper), Image Processing Techniques and Applications (1 paper), Reservoir Engineering and Simulation Methods (1 paper), Image and Signal Denoising Methods (1 paper) and Advanced Image Processing Techniques (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (116 citations), Statistics, Probability and Uncertainty (43 citations), Media Technology (30 citations), Numerical Analysis (15 citations) and Computer Vision and Pattern Recognition (54 citations). David Widemann has collaborated with scholars based in United States and Norway. Frequent co-authors include Youngkyu Kim, Tarek I. Zohdi, Youngsoo Choi, Adam Moody, Brendt Wohlberg, Youzuo Lin, Felix Krahmer, Tarek M. Taha, Md Zahangir Alom and Brian Van Essen. Their work appears in journals such as Journal of Biomedical Informatics, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, PLoS ONE, Journal of Computational Physics and Proceedings of the AAAI Conference on Artificial Intelligence.
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.