Markus Svensén
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Control and Systems Engineering top 5%
- Signal Processing top 2%
- Physiology top 10%
- Co-authors
- Chris BishopChristopher K. I. WilliamsOlga FinkWan-Jui LeeMélanie DucoffeQin WangPierre DersinFrithjof Kruggel
- Topics
- Neural Networks and Applications (4 papers)Neural dynamics and brain function (2 papers)Fault Detection and Control Systems (2 papers)
- Journals
- NeuroImageAmerican Journal of Respiratory and Critical Care MedicineIEEE Transactions on Medical Imaging
- Partner nations
- United KingdomGermanyFrance
In The Last Decade
Markus Svensén
16 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 158
- Artificial Intelligence 756
- Computer Vision and Pattern Recognition 527
- Control and Systems Engineering 327
- Signal Processing 297
- Physiology 269
Countries citing papers authored by Markus Svensén
This map shows the geographic impact of Markus Svensén'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 Markus Svensén with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Svensén more than expected).
Fields of papers citing papers by Markus Svensén
This network shows the impact of papers produced by Markus Svensén. 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 Markus Svensén. The network helps show where Markus Svensén may publish in the future.
Co-authorship network of co-authors of Markus Svensén
This figure shows the co-authorship network connecting the top 25 collaborators of Markus Svensén. A scholar is included among the top collaborators of Markus Svensén 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 Markus Svensén. Markus Svensén is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Potential, challenges and future directions for deep learning in prognostics and health management applicationsbreakdown → | 357 |
| 2 | 13 | |
| 3 | Broad vs Narrow: Modelling Strategies for Online Behavioural Targeting | 1 |
| 4 | Proceedings of the Fifth International Workshop on Data Mining and Audience Intelligence for Advertising (ADKDD) | 6 |
| 5 | 311 | |
| 6 | 183 | |
| 7 | 46 | |
| 8 | 110 | |
| 9 | 5 | |
| 10 | 12 | |
| 11 | 37 | |
| 12 | GTM: The Generative Topographic Mappingbreakdown → | 875 |
| 13 | 139 | |
| 14 | Proceedings 1997 Workshop on Self-Organizing Maps | 17 |
| 15 | Magnification factors for the SOM and GTM algorithms | 18 |
| 16 | EM Optimization of Latent-Variable Density Models | 11 |
About Markus Svensén
Markus Svensén is a scholar working on Statistics and Probability, Artificial Intelligence and Signal Processing, having authored 16 papers that have together received 2.1k indexed citations. Recurring topics across this work include Neural Networks and Applications (4 papers), Neural dynamics and brain function (2 papers) and Fault Detection and Control Systems (2 papers). The work is most often cited by research in Signal Processing (297 citations), Computer Vision and Pattern Recognition (527 citations) and Artificial Intelligence (756 citations). Markus Svensén has collaborated with scholars based in United Kingdom, Germany and France. Frequent co-authors include Chris Bishop, Christopher K. I. Williams, Olga Fink, Wan-Jui Lee, Mélanie Ducoffe, Qin Wang, Pierre Dersin, Frithjof Kruggel, Adnan Ćustović and David Heckerman. Their work appears in journals such as NeuroImage, American Journal of Respiratory and Critical Care Medicine and IEEE Transactions on Medical Imaging.
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.