Thomas Elsken

4.0k total citations · 1 hit paper
14 papers, 467 citations indexed

About

Thomas Elsken is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Control and Systems Engineering. According to data from OpenAlex, Thomas Elsken has authored 14 papers receiving a total of 467 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 6 papers in Computational Theory and Mathematics and 5 papers in Control and Systems Engineering. Recurrent topics in Thomas Elsken's work include Stability and Controllability of Differential Equations (5 papers), Advanced Mathematical Modeling in Engineering (5 papers) and Neural Networks and Applications (3 papers). Thomas Elsken is often cited by papers focused on Stability and Controllability of Differential Equations (5 papers), Advanced Mathematical Modeling in Engineering (5 papers) and Neural Networks and Applications (3 papers). Thomas Elsken collaborates with scholars based in Germany and United Kingdom. Thomas Elsken's co-authors include Frank Hutter, Jan Hendrik Metzen, Thomas Brox, Arber Zela, Yassine Marrakchi, Tonmoy Saikia, Martino Prizzi, Rohit Mohan, Benedikt Staffler and Abhinav Valada and has published in prestigious journals such as International Journal of Computer Vision, Neural Networks and Journal of Mathematical Analysis and Applications.

In The Last Decade

Thomas Elsken

14 papers receiving 444 citations

Hit Papers

Neural Architecture Search: A Survey 2019 2026 2021 2023 2019 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Thomas Elsken Germany 8 277 209 55 46 40 14 467
Chris Darken United States 7 170 0.6× 80 0.4× 22 0.4× 54 1.2× 37 0.9× 10 359
Yunlong Feng China 13 203 0.7× 149 0.7× 25 0.5× 94 2.0× 22 0.6× 29 544
Shizhong Liao China 13 249 0.9× 166 0.8× 39 0.7× 27 0.6× 21 0.5× 68 457
Tuo Zhao United States 13 176 0.6× 115 0.6× 22 0.4× 44 1.0× 42 1.1× 51 479
Rong Ge United States 11 191 0.7× 144 0.7× 74 1.3× 17 0.4× 42 1.1× 28 579
J. Koplowitz United States 12 115 0.4× 287 1.4× 40 0.7× 24 0.5× 60 1.5× 34 455
D. A. Podoprikhin Russia 6 242 0.9× 176 0.8× 31 0.6× 11 0.2× 23 0.6× 11 411
Changyou Chen United States 15 425 1.5× 194 0.9× 18 0.3× 22 0.5× 27 0.7× 47 705
István Dénes Germany 6 148 0.5× 99 0.5× 20 0.4× 46 1.0× 49 1.2× 12 454
Mert Pilancı United States 9 186 0.7× 59 0.3× 48 0.9× 20 0.4× 22 0.6× 47 368

Countries citing papers authored by Thomas Elsken

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Thomas Elsken

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Elsken. A scholar is included among the top collaborators of Thomas Elsken 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 Thomas Elsken. Thomas Elsken is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Mohan, Rohit, Thomas Elsken, Arber Zela, et al.. (2023). Neural Architecture Search for Dense Prediction Tasks in Computer Vision. International Journal of Computer Vision. 131(7). 1784–1807. 11 indexed citations
2.
Zela, Arber, Thomas Elsken, Tonmoy Saikia, et al.. (2020). Understanding and Robustifying Differentiable Architecture Search. arXiv (Cornell University). 41 indexed citations
3.
Elsken, Thomas, Jan Hendrik Metzen, & Frank Hutter. (2019). Neural Architecture Search: A Survey. arXiv (Cornell University). 20(55). 1–21. 338 indexed citations breakdown →
4.
Elsken, Thomas, Jan Hendrik Metzen, & Frank Hutter. (2018). Multi-objective Architecture Search for CNNs.. arXiv (Cornell University). 10 indexed citations
5.
Elsken, Thomas, Jan Hendrik Metzen, & Frank Hutter. (2018). Simple and efficient architecture search for Convolutional Neural Networks. International Conference on Learning Representations. 16 indexed citations
6.
Elsken, Thomas. (2005). Continuity of attractors for net-shaped thin domains. Topological Methods in Nonlinear Analysis. 26(2). 315–315. 13 indexed citations
7.
Elsken, Thomas. (2004). Attractors for reaction–diffusion equations on thin domains whose linear part is non-self-adjoint. Journal of Differential Equations. 206(1). 94–126. 12 indexed citations
8.
Elsken, Thomas. (2004). A reaction-diffusion equation on a net-shaped thin domain. Studia Mathematica. 165(2). 159–199. 5 indexed citations
9.
Elsken, Thomas. (2002). Limiting behavior of attractors for systems on thin domains. Hiroshima Mathematical Journal. 32(3). 6 indexed citations
10.
Elsken, Thomas & Martino Prizzi. (2002). Characterization of the limit of some higher dimensional thin domain problems. Topological Methods in Nonlinear Analysis. 20(1). 151–151. 3 indexed citations
11.
Elsken, Thomas. (2001). The Region of (In)Stability of a 2-Delay Equation Is Connected. Journal of Mathematical Analysis and Applications. 261(2). 497–526. 3 indexed citations
12.
Elsken, Thomas. (1999). Smaller nets may perform better: special transfer functions. Neural Networks. 12(4-5). 627–645. 1 indexed citations
13.
Elsken, Thomas. (1997). Even on Finite Test Sets Smaller Nets may Perform Better. Neural Networks. 10(2). 369–385. 7 indexed citations
14.
Elsken, Thomas, D. B. Pearson, & Peter M. Robinson. (1996). Approximate Monotonicity: Theory and Applications. Journal of the London Mathematical Society. 53(3). 489–502. 1 indexed citations

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.

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