Matthias Bollhöfer

1.5k total citations
44 papers, 800 citations indexed

About

Matthias Bollhöfer is a scholar working on Computational Theory and Mathematics, Atomic and Molecular Physics, and Optics and Computational Mechanics. According to data from OpenAlex, Matthias Bollhöfer has authored 44 papers receiving a total of 800 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Computational Theory and Mathematics, 20 papers in Atomic and Molecular Physics, and Optics and 16 papers in Computational Mechanics. Recurrent topics in Matthias Bollhöfer's work include Matrix Theory and Algorithms (30 papers), Electromagnetic Scattering and Analysis (19 papers) and Advanced Numerical Methods in Computational Mathematics (11 papers). Matthias Bollhöfer is often cited by papers focused on Matrix Theory and Algorithms (30 papers), Electromagnetic Scattering and Analysis (19 papers) and Advanced Numerical Methods in Computational Mathematics (11 papers). Matthias Bollhöfer collaborates with scholars based in Germany, Switzerland and Spain. Matthias Bollhöfer's co-authors include Olaf Schenk, Yousef Saad, Rudolf A. Römer, Yvan Notay, Simon Scheidegger, Marcus J. Grote, Christoph Jungemann, Enrique S. Quintana–Ort́ı, José I. Aliaga and B. Meinerzhagen and has published in prestigious journals such as Journal of Applied Physics, IEEE Transactions on Pattern Analysis and Machine Intelligence and Mathematics of Computation.

In The Last Decade

Matthias Bollhöfer

43 papers receiving 711 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthias Bollhöfer Germany 15 370 344 248 187 114 44 800
Takeshi Iwashita Japan 15 222 0.6× 171 0.5× 128 0.5× 305 1.6× 29 0.3× 89 583
Wayne Joubert United States 15 196 0.5× 337 1.0× 173 0.7× 60 0.3× 153 1.3× 50 633
Diederik R. Fokkema Netherlands 8 428 1.2× 582 1.7× 276 1.1× 230 1.2× 328 2.9× 9 966
Steffen Börm Germany 16 788 2.1× 428 1.2× 317 1.3× 512 2.7× 61 0.5× 41 1.1k
Scott MacLachlan Canada 22 188 0.5× 649 1.9× 926 3.7× 280 1.5× 339 3.0× 85 1.4k
David Day United States 11 152 0.4× 298 0.9× 204 0.8× 145 0.8× 166 1.5× 31 567
Eugene E. Tyrtyshnikov Russia 11 123 0.3× 240 0.7× 187 0.8× 65 0.3× 62 0.5× 21 644
P. Sonneveld Netherlands 10 418 1.1× 752 2.2× 519 2.1× 209 1.1× 363 3.2× 19 1.2k
William F. Mitchell United States 15 120 0.3× 254 0.7× 590 2.4× 186 1.0× 132 1.2× 36 939
Reinhard Nabben Germany 17 208 0.6× 577 1.7× 305 1.2× 198 1.1× 226 2.0× 52 801

Countries citing papers authored by Matthias Bollhöfer

Since Specialization
Citations

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

Fields of papers citing papers by Matthias Bollhöfer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthias Bollhöfer

This figure shows the co-authorship network connecting the top 25 collaborators of Matthias Bollhöfer. A scholar is included among the top collaborators of Matthias Bollhöfer 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 Matthias Bollhöfer. Matthias Bollhöfer 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.
Bollhöfer, Matthias, et al.. (2023). Sparse Quadratic Approximation for Graph Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(9). 11256–11269. 1 indexed citations
2.
Römer, Ulrich, et al.. (2021). An adaptive sparse grid rational Arnoldi method for uncertainty quantification of dynamical systems in the frequency domain. International Journal for Numerical Methods in Engineering. 122(20). 5487–5511. 3 indexed citations
3.
Bollhöfer, Matthias, et al.. (2021). Block-enhanced precision matrix estimation for large-scale datasets. Journal of Computational Science. 53. 101389–101389. 3 indexed citations
4.
Sanan, Patrick, Dave A. May, Matthias Bollhöfer, & Olaf Schenk. (2020). Pragmatic solvers for 3D Stokes and elasticity problems with heterogeneous coefficients: evaluating modern incomplete LDL T preconditioners. Solid Earth. 11(6). 2031–2045. 2 indexed citations
5.
Bollhöfer, Matthias, et al.. (2019). A block version of left-looking AINV preconditioner with one by one or two by two block pivots. Applied Mathematics and Computation. 350. 366–385. 2 indexed citations
6.
Bebendorf, Mario, et al.. (2016). On the spectral equivalence of hierarchical matrix preconditioners for elliptic problems. Mathematics of Computation. 85(302). 2839–2861. 4 indexed citations
7.
Benner, Peter, Matthias Bollhöfer, Daniel Kreßner, Christian Mehl, & Tatjana Stykel. (2015). Numerical algebra, matrix theory, differential-algebraic equations and control theory : Festschrift in honor of Volker Mehrmann. Springer eBooks. 3 indexed citations
8.
Aliaga, José I., et al.. (2014). Leveraging Data-Parallelism in ILUPACK using Graphics Processors. 119–126. 4 indexed citations
9.
Bonfiglioli, Aldo, M. Sergio Campobasso, Bruno Carpentieri, & Matthias Bollhöfer. (2012). A parallel 3D unstructured implicit RANS solver for compressible and incompressible CFD simulations. Lecture notes in computer science. 1 indexed citations
10.
Bollhöfer, Matthias, et al.. (2010). An alternative way of solving large Lyapunov equations. PAMM. 10(1). 547–548. 4 indexed citations
11.
Hong, Sung‐Min, Christoph Jungemann, & Matthias Bollhöfer. (2008). A deterministic Boltzmann equation solver for two-dimensional semiconductor devices. 293–296. 6 indexed citations
12.
Schenk, Olaf, Matthias Bollhöfer, & Rudolf A. Römer. (2008). On Large-Scale Diagonalization Techniques for the Anderson Model of Localization. SIAM Review. 50(1). 91–112. 103 indexed citations
13.
Schenk, Olaf, Matthias Bollhöfer, & Rudolf A. Römer. (2007). On large‐scale diagonalization techniques for the Anderson model of localization. PAMM. 7(1). 1021003–1021004. 1 indexed citations
14.
Bollhöfer, Matthias & Yvan Notay. (2007). JADAMILU: a software code for computing selected eigenvalues of large sparse symmetric matrices. Computer Physics Communications. 177(12). 951–964. 82 indexed citations
15.
Griewank, Andreas, et al.. (2006). On the Efficient Update of Rectangular LU Factorizations subject to Low Rank Modifications. DepositOnce. 26. 161–177. 8 indexed citations
16.
Horesh, Lior, et al.. (2006). MULTILEVEL PRECONDITIONING FOR 3D LARGE-SCALE SOFT-FIELD MEDICAL APPLICATIONS MODELLING. 13 indexed citations
17.
Bollhöfer, Matthias & Olaf Schenk. (2006). Combinatorial Aspects in Sparse Elimination Methods. GAMM-Mitteilungen. 29(2). 342–367. 1 indexed citations
18.
Jungemann, Christoph, Anh-Tuan Pham, B. Meinerzhagen, Christian Ringhofer, & Matthias Bollhöfer. (2006). Stable discretization of the Boltzmann equation based on spherical harmonics, box integration, and a maximum entropy dissipation principle. Journal of Applied Physics. 100(2). 51 indexed citations
19.
Bollhöfer, Matthias. (2003). A Robust and Efficient ILU that Incorporates the Growth of the Inverse Triangular Factors. SIAM Journal on Scientific Computing. 25(1). 86–103. 32 indexed citations
20.
Bollhöfer, Matthias. (2001). A robust ILU with pivoting based on monitoring the growth of the inverse factors. Linear Algebra and its Applications. 338(1-3). 201–218. 48 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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