Thomas Elsken
Impact in
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- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Artificial Intelligence top 5%
- Machine Learning and Data Classification
- Domain Adaptation and Few-Shot Learning
- Neural Networks and Applications
- Adversarial Robustness in Machine Learning
Papers in
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- Adversarial Robustness in Machine Learning 3
- Neural Networks and Applications 3
- Domain Adaptation and Few-Shot Learning 2
- Machine Learning and Data Classification 2
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- Advanced Mathematical Modeling in Engineering 5
- Co-authors
- Frank Hutter (5 shared papers)Jan Hendrik Metzen (4 shared papers)Thomas Brox (2 shared papers)Arber Zela (2 shared papers)Yassine Marrakchi (1 shared paper)Tonmoy Saikia (1 shared paper)Abhinav Valada (1 shared paper)Benedikt Staffler (1 shared paper)
- Journals
- Topological Methods in Nonlinear Analysis (2 papers)Neural Networks (2 papers)Hiroshima Mathematical Journal (1 paper)Journal of Differential Equations (1 paper)Journal of the London Mathematical Society (1 paper)
- Partner nations
- GermanyRussiaUnited Kingdom
In The Last Decade
Thomas Elsken
15 papers receiving 451 citations
Thomas Elsken's Hit Papers
Peers
Comparison fields: 5 of 88
- Computer Vision and Pattern Recognition 209
- Artificial Intelligence 275
- Computational Theory and Mathematics 54
- Computational Mathematics 2
- Health Informatics 3
Countries citing papers authored by Thomas Elsken
This map shows the geographic impact of Thomas Elsken'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 Thomas Elsken with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Elsken more than expected).
Fields of papers citing papers by Thomas Elsken
This network shows the impact of papers produced by Thomas Elsken. 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 Thomas Elsken. The network helps show where Thomas Elsken may publish in the future.
Co-authors
The 12 scholars most cited alongside Thomas Elsken, 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 | Neural Architecture Search: A Survey Hit paper breakdown → | 2019 | 340 |
| 2 | Understanding and Robustifying Differentiable Architecture Search | 2020 | 41 |
| 3 | Simple and efficient architecture search for Convolutional Neural Networks | 2018 | 16 |
| 4 | 2023 | 12 | |
| 5 | 2004 | 12 | |
| 6 | 2005 | 12 | |
| 7 | Multi-objective Architecture Search for CNNs. | 2018 | 10 |
| 8 | 1997 | 7 | |
| 9 | 2002 | 6 | |
| 10 | 2004 | 5 | |
| 11 | 2024 | 4 | |
| 12 | 2001 | 3 | |
| 13 | 2002 | 3 | |
| 14 | 1996 | 1 | |
| 15 | 1999 | 1 |
About Thomas Elsken
Thomas Elsken is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Control and Systems Engineering, Computer Vision and Pattern Recognition and Applied Mathematics, having authored 15 papers that have together received 473 indexed citations. Recurring topics across this work include Advanced Mathematical Modeling in Engineering (5 papers), Stability and Controllability of Differential Equations (5 papers), Adversarial Robustness in Machine Learning (3 papers), Neural Networks and Applications (3 papers), Advanced Neural Network Applications (3 papers), Domain Adaptation and Few-Shot Learning (2 papers), Machine Learning and Data Classification (2 papers) and Nonlinear Differential Equations Analysis (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (209 citations), Artificial Intelligence (275 citations), Computational Theory and Mathematics (54 citations), Computational Mathematics (2 citations) and Health Informatics (3 citations). Thomas Elsken has collaborated with scholars based in Germany, Russia and United Kingdom. Frequent co-authors include Frank Hutter, Jan Hendrik Metzen, Thomas Brox, Arber Zela, Yassine Marrakchi, Tonmoy Saikia, Abhinav Valada, Benedikt Staffler, Rohit Mohan and Martino Prizzi. Their work appears in journals such as Topological Methods in Nonlinear Analysis, Neural Networks, Hiroshima Mathematical Journal, Journal of Differential Equations and Journal of the London 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.