Karsten Kahl

643 total citations
28 papers, 329 citations indexed

About

Karsten Kahl is a scholar working on Computational Theory and Mathematics, Computational Mechanics and Electrical and Electronic Engineering. According to data from OpenAlex, Karsten Kahl has authored 28 papers receiving a total of 329 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computational Theory and Mathematics, 14 papers in Computational Mechanics and 6 papers in Electrical and Electronic Engineering. Recurrent topics in Karsten Kahl's work include Matrix Theory and Algorithms (17 papers), Advanced Numerical Methods in Computational Mathematics (12 papers) and Quantum Chromodynamics and Particle Interactions (6 papers). Karsten Kahl is often cited by papers focused on Matrix Theory and Algorithms (17 papers), Advanced Numerical Methods in Computational Mathematics (12 papers) and Quantum Chromodynamics and Particle Interactions (6 papers). Karsten Kahl collaborates with scholars based in Germany, United States and Japan. Karsten Kahl's co-authors include Andreas Frommer, James Brannick, Björn Leder, Matthias Rottmann, Achi Brandt, Stefan Krieg, I. M. Livshits, Matthias Rottmann, Constantia Alexandrou and Simone Bacchio and has published in prestigious journals such as International Journal of Computer Vision, Computer Physics Communications and SIAM Journal on Numerical Analysis.

In The Last Decade

Karsten Kahl

26 papers receiving 311 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Karsten Kahl Germany 8 148 126 90 42 28 28 329
James Brannick United States 10 134 0.9× 220 1.7× 191 2.1× 43 1.0× 39 1.4× 24 404
Willi Schönauer Germany 7 153 1.0× 74 0.6× 108 1.2× 46 1.1× 74 2.6× 27 362
Pierre Ramet France 7 117 0.8× 85 0.7× 77 0.9× 34 0.8× 23 0.8× 24 313
Meraj Ali Khan Saudi Arabia 11 29 0.2× 36 0.3× 42 0.5× 37 0.9× 22 0.8× 121 432
Ronald Babich United States 10 597 4.0× 57 0.5× 21 0.2× 38 0.9× 3 0.1× 15 725
Huaiyu Jian China 16 14 0.1× 125 1.0× 39 0.4× 21 0.5× 30 1.1× 60 725
Robert Speck Germany 10 26 0.2× 61 0.5× 133 1.5× 43 1.0× 101 3.6× 23 270
Min-Chun Hong Australia 13 26 0.2× 247 2.0× 89 1.0× 9 0.2× 24 0.9× 52 762
Werner M. Seiler Germany 10 32 0.2× 212 1.7× 59 0.7× 13 0.3× 91 3.3× 60 379
Veerle Ledoux Belgium 10 37 0.3× 76 0.6× 27 0.3× 99 2.4× 127 4.5× 21 315

Countries citing papers authored by Karsten Kahl

Since Specialization
Citations

This map shows the geographic impact of Karsten Kahl'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 Karsten Kahl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karsten Kahl more than expected).

Fields of papers citing papers by Karsten Kahl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Karsten Kahl. 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 Karsten Kahl. The network helps show where Karsten Kahl may publish in the future.

Co-authorship network of co-authors of Karsten Kahl

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

All Works

20 of 20 papers shown
1.
Kahl, Karsten, et al.. (2025). LMD: Light-Weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds. International Journal of Computer Vision. 133(7). 4349–4365. 1 indexed citations
2.
Brannick, James, et al.. (2024). Constrained Local Approximate Ideal Restriction for Advection-Diffusion Problems. SIAM Journal on Scientific Computing. 46(5). S96–S122. 1 indexed citations
3.
Kahl, Karsten, et al.. (2024). Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection. 366–374. 1 indexed citations
4.
5.
Frommer, Andreas, et al.. (2023). Krylov Subspace Restarting for Matrix Laplace Transforms. SIAM Journal on Matrix Analysis and Applications. 44(2). 693–717. 1 indexed citations
6.
Gottschalk, Hanno & Karsten Kahl. (2021). Coarsening in algebraic multigrid using Gaussian processes. ETNA - Electronic Transactions on Numerical Analysis. Oesterreichisches Musiklexikon online (Institut für kunst- und musikhistorische Forschungen der Österreichischen Akademie der Wissenschaften). 4 indexed citations
7.
Kreßner, Daniel, et al.. (2018). Multigrid methods combined with low-rank approximation for tensor-structured Markov chains. ETNA - Electronic Transactions on Numerical Analysis. Oesterreichisches Musiklexikon online (Institut für kunst- und musikhistorische Forschungen der Österreichischen Akademie der Wissenschaften). 2 indexed citations
8.
Brannick, James, et al.. (2018). Optimal Interpolation and Compatible Relaxation in Classical Algebraic Multigrid. SIAM Journal on Scientific Computing. 40(3). A1473–A1493. 17 indexed citations
9.
Ulybyshev, Maksim, et al.. (2018). Schur complement solver for Quantum Monte-Carlo simulations of strongly interacting fermions. Computer Physics Communications. 236. 118–127. 11 indexed citations
10.
Kahl, Karsten, et al.. (2018). Geometric Multigrid for the Tight-Binding Hamiltonian of Graphene. SIAM Journal on Numerical Analysis. 56(1). 499–519.
11.
Kahl, Karsten. (2018). Adaptive Algebraic Multigrid for Lattice QCD Computations. 1 indexed citations
12.
Kahl, Karsten, et al.. (2016). The deflated conjugate gradient method: Convergence, perturbation and accuracy. Linear Algebra and its Applications. 515. 111–129. 4 indexed citations
13.
Simeth, Jakob, Gunnar Bali, Sara Collins, et al.. (2016). (Approximate) Low-Mode Averaging with a new Multigrid Eigensolver. 350–350. 3 indexed citations
14.
Brandt, Achi, et al.. (2016). Bootstrap Algebraic Multigrid: status report, open problems, and outlook. 9 indexed citations
15.
Brannick, James, et al.. (2015). Multigrid preconditioning for the overlap operator in lattice QCD. Numerische Mathematik. 132(3). 463–490. 15 indexed citations
16.
Brannick, James & Karsten Kahl. (2014). Bootstrap Algebraic Multigrid for the 2D Wilson Dirac system. SIAM Journal on Scientific Computing. 36(3). B321–B347. 6 indexed citations
17.
Rottmann, Matthias, Andreas Frommer, Karsten Kahl, Stefan Krieg, & Björn Leder. (2012). Aggregation-based Multilevel Methods for Lattice QCD. 46–46. 1 indexed citations
18.
Bolten, Matthias, et al.. (2011). A Bootstrap Algebraic Multilevel Method for Markov Chains. SIAM Journal on Scientific Computing. 33(6). 3425–3446. 11 indexed citations
19.
Brannick, James, Andreas Frommer, Karsten Kahl, Scott MacLachlan, & Ludmil Zikatanov. (2010). Adaptive reduction-based multigrid for nearly singular and highly disordered physical systems. ETNA - Electronic Transactions on Numerical Analysis. 37. 276–295. 7 indexed citations
20.
Bolten, Matthias, et al.. (2010). Algebraic multigrid methods for Laplacians of graphs. Linear Algebra and its Applications. 434(11). 2225–2243. 5 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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