Andrew Knyazev

2.6k citations
74 papers · 1.6k indexed · 1 hit paper · h-index 19

Andrew Knyazev

67 papers receiving 1.4k citations

Hit Papers

Toward the Optimal Preconditioned Eigensolver: Locally Op...4962001202620092017100200300400

Peers

Andrew Knyazev
Comparison fields: 5 of 110
  • Computational Mathematics 41
  • Computational Theory and Mathematics 809
  • Numerical Analysis 260
  • Computational Mechanics 514
  • Mathematical Physics 145
Replace Yvan Notay with:
Yvan Notay Belgium
Jane Cullum United States
J. Ruge United States
Folkmar Bornemann Germany
Gérard Meurant France
Thomas Huckle Germany
Anne Greenbaum United States
Zdeněk Strakoš Czechia
Andreas Frommer Germany
Jörg Liesen Germany
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Citations per field
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Citations per year

Countries citing papers authored by Andrew Knyazev

Since Specialization
Citations

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

Fields of papers citing papers by Andrew Knyazev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Andrew Knyazev, 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 Andrew Knyazev Line = papers co-authored together Andrew Knyazev links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20230
3 20212
4 20202
5
Signed Laplacian for spectral clustering revisited.
201710
6 20171
7 20173
8 201613
9 20161
10 20161
11 20154
12 20141
13
Principal angles between subspaces and their tangents
201214
14 201018
15 20060
16 200623
17 200512
18 200262
19
Efficient solution of symmetric eigenvalue problems using multigridpreconditioners in the locally optimal block conjugate gradient method
200147
20
Preconditioned Eigensolvers - an Oxymoron?
199874

About Andrew Knyazev

Andrew Knyazev is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Computational Mechanics, having authored 74 papers that have together received 1.6k indexed citations. Recurring topics across this work include Matrix Theory and Algorithms (37 papers), Advanced Numerical Methods in Computational Mathematics (25 papers), Advanced Optimization Algorithms Research (11 papers), Numerical methods in inverse problems (10 papers), Advanced Control Systems Optimization (10 papers), Electromagnetic Scattering and Analysis (9 papers), Control Systems and Identification (7 papers) and Advanced Mathematical Modeling in Engineering (6 papers). The work is most often cited by research in Computational Mathematics (41 citations), Computational Theory and Mathematics (809 citations) and Numerical Analysis (260 citations). Andrew Knyazev has collaborated with scholars based in United States, Russia and Germany. Frequent co-authors include Merico E. Argentati, Klaus Neymeyr, G. Zérah, François Bottin, Ilya Lashuk, John E. Osborn, Joseph E. Pasciak, James H. Bramble, Ping Zhu and Rien Quirynen. Their work appears in journals such as SHILAP Revista de lepidopterología, Physical Chemistry Chemical Physics and Computer Methods in Applied Mechanics and Engineering.

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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