E. Grimme

1.5k citations
12 papers · 488 · h-index 6

Impact in

Papers in

E. Grimme

12 papers receiving 445 citations

Peers

E. Grimme
Comparison fields: 5 of 45
  • Numerical Analysis 177
  • Statistical and Nonlinear Physics 326
  • Statistics, Probability and Uncertainty 99
  • Computational Theory and Mathematics 112
  • Computational Mathematics 3
Replace Hyung‐Chun Lee with:
Hyung‐Chun Lee South Korea
Yanlai Chen United States
R. Seydel Germany
Younès Chahlaoui Saudi Arabia
Jakob Zech Switzerland
T. A. Porsching United States
B.B. King United States
Heike Faßbender Germany
Vadim Adamjan Ukraine
Julia Novo Spain
E. Grimme relative to Hyung‐Chun Lee South Korea Hyung‐Chun Lee's profile →
Citations per field
00.5×1.5×1.9×
Hyung‐Chun Lee · 1×
Citations per year

Countries citing papers authored by E. Grimme

Since Specialization
Citations

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

Fields of papers citing papers by E. Grimme

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside E. Grimme, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with E. Grimme Line = papers co-authored together E. Grimme links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 1994155
2 1996120
3 199981
4 199456
5 200240
6
On some recent developments in projection-based model reduction
199820
7 20024
8
On some modifications of the Lanczos algorithm and the relation with Padé approximations
19974
9 20093
10
An Implicitly Restarted Lanczos Method for the Model Reduction of Stable, Large-Scale Systems
19932
11 20052
12 19961

About E. Grimme

E. Grimme is a scholar working on Statistical and Nonlinear Physics, Computational Theory and Mathematics, Control and Systems Engineering, Electrical and Electronic Engineering and Applied Mathematics, having authored 12 papers that have together received 488 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (8 papers), Control Systems and Identification (4 papers), Matrix Theory and Algorithms (4 papers), Real-time simulation and control systems (3 papers), Numerical Methods and Algorithms (3 papers), Mathematical functions and polynomials (1 paper), Electromagnetic Simulation and Numerical Methods (1 paper) and NMR spectroscopy and applications (1 paper). The work is most often cited by research in Numerical Analysis (177 citations), Statistical and Nonlinear Physics (326 citations), Statistics, Probability and Uncertainty (99 citations), Computational Theory and Mathematics (112 citations) and Computational Mathematics (3 citations). E. Grimme has collaborated with scholars based in United States, Belgium and Switzerland. Frequent co-authors include Paul Van Dooren, Kyle A. Gallivan, D. C. Sorensen, Eric Michielssen, Daniel S. Weile, Åke Björck, A.C. Antoulas, Georges Gielen, Martin O’Leary and W. J. Wong. Their work appears in journals such as Applied Mathematics Letters, BIT Numerical Mathematics, Numerical Algorithms, IFAC Proceedings Volumes and Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign).

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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