Christine De Mol
- Computational Mechanics top 0.2%
- Computer Vision and Pattern Recognition top 0.5%
- Biomedical Engineering top 2%
- Mathematical Physics top 1%
- Radiology, Nuclear Medicine and Imaging top 2%
- Co-authors
- Ingrid DaubechiesMichel DefriseDomenico GiannoneM. BerteroE. R. PikeLucrezia ReichlinIgnace LorisAlessandro Verri
- Topics
- Numerical methods in inverse problems (19 papers)Image and Signal Denoising Methods (14 papers)Sparse and Compressive Sensing Techniques (11 papers)
- Journals
- Proceedings of the National Academy of SciencesIEEE Transactions on Image ProcessingOptics Letters
- Partner nations
- BelgiumItalyUnited Kingdom
In The Last Decade
Christine De Mol
44 papers receiving 4.5k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Computational Mechanics 2.2k
- Computer Vision and Pattern Recognition 1.5k
- Biomedical Engineering 1.1k
- Mathematical Physics 653
- Radiology, Nuclear Medicine and Imaging 526
Countries citing papers authored by Christine De Mol
This map shows the geographic impact of Christine De Mol'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 Christine De Mol with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christine De Mol more than expected).
Fields of papers citing papers by Christine De Mol
This network shows the impact of papers produced by Christine De Mol. 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 Christine De Mol. The network helps show where Christine De Mol may publish in the future.
Co-authorship network of co-authors of Christine De Mol
This figure shows the co-authorship network connecting the top 25 collaborators of Christine De Mol. A scholar is included among the top collaborators of Christine De Mol based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Christine De Mol. Christine De Mol is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | Optimal Combination of Survey Forecasts | 3 |
| 4 | 43 | |
| 5 | 46 | |
| 6 | Analysis of Elastic-Net Regularization in Learning Theory | 1 |
| 7 | 29 | |
| 8 | Inverse imaging with mixed penalties | 8 |
| 9 | An iterative thresholding algorithm for linear inverse problems with a sparsity constraintbreakdown → | 3180 |
| 10 | 4 | |
| 11 | Wavelet versus Fourier analysis of Philautus spp. croaking. | 0 |
| 12 | Super-resolution by data inversion | 23 |
| 13 | Mapping 2-D defects in a conductive half-space by eigenfunction expansions in K-space of Fourier-Laplace transforms | 1 |
| 14 | 9 | |
| 15 | 4 | |
| 16 | 158 | |
| 17 | Positive regularised solutions in electromagnetic inverse scattering | 2 |
| 18 | Iterative inversion of experimental data in weighted spaces | 2 |
| 19 | 32 | |
| 20 | 9 |
About Christine De Mol
Christine De Mol is a scholar working on Mathematical Physics, Computer Vision and Pattern Recognition and Applied Mathematics, having authored 49 papers that have together received 4.8k indexed citations. Recurring topics across this work include Numerical methods in inverse problems (19 papers), Image and Signal Denoising Methods (14 papers) and Sparse and Compressive Sensing Techniques (11 papers). The work is most often cited by research in Computational Mechanics (2.2k citations), Computer Vision and Pattern Recognition (1.5k citations) and Mathematical Physics (653 citations). Christine De Mol has collaborated with scholars based in Belgium, Italy and United Kingdom. Frequent co-authors include Ingrid Daubechies, Michel Defrise, Domenico Giannone, M. Bertero, E. R. Pike, Lucrezia Reichlin, Ignace Loris, Alessandro Verri, Francesca Odone and Sofia Mosci. Their work appears in journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Image Processing and Optics Letters.
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.