Daniel Kreßner

158 papers receiving 3.1k citations

Daniel Kreßner's Hit Papers

A literature survey of low‐rank tensor approximation techniques 2013 · 422 citations
4220+4+8Years since publication100200300400

Peers

Daniel Kreßner
Comparison fields: 5 of 97
  • Computational Mathematics 1.1k
  • Numerical Analysis 893
  • Computational Theory and Mathematics 1.8k
  • Statistical and Nonlinear Physics 772
  • Computational Mechanics 847
Replace Karl Meerbergen with:
Karl Meerbergen Belgium
Marc Van Barel Belgium
Lek‐Heng Lim United States
Valeria Simoncini Italy
Zhaojun Bai United States
Lars Grasedyck Germany
Boris N. Khoromskij Germany
Stanley C. Eisenstat United States
Sven J. Hammarling United Kingdom
Moody T. Chu United States
Daniel Kreßner relative to Karl Meerbergen Belgium Karl Meerbergen's profile →
Citations per field
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Karl Meerbergen · 1×
Citations per year

Countries citing papers authored by Daniel Kreßner

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Kreßner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 171 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A literature survey of low‐rank tensor approximation techniques
Hit paper breakdown →
2013422
2 2013207
3 2011141
4 2010131
5 2008114
6 200981
7 200580
8 200872
9 201463
10 201258
11 201555
12 201454
13 200651
14 201151
15 201448
16 201141
17 200640
18 200538
19 200135
20 201035

About Daniel Kreßner

Daniel Kreßner is a scholar working on Computational Theory and Mathematics, Computational Mathematics, Numerical Analysis, Statistical and Nonlinear Physics and Computational Mechanics, having authored 171 papers that have together received 3.3k indexed citations. Recurring topics across this work include Matrix Theory and Algorithms (123 papers), Tensor decomposition and applications (48 papers), Numerical methods for differential equations (40 papers), Model Reduction and Neural Networks (38 papers), Sparse and Compressive Sensing Techniques (27 papers), Electromagnetic Scattering and Analysis (27 papers), Advanced Optimization Algorithms Research (18 papers) and Advanced Numerical Methods in Computational Mathematics (15 papers). The work is most often cited by research in Computational Mathematics (1.1k citations), Numerical Analysis (893 citations), Computational Theory and Mathematics (1.8k citations), Statistical and Nonlinear Physics (772 citations) and Computational Mechanics (847 citations). Daniel Kreßner has collaborated with scholars based in Switzerland, Germany and Sweden. Frequent co-authors include Christine Tobler, Lars Grasedyck, Bart Vandereycken, Michael Steinlechner, Bo Kågström, Peter Benner, André Uschmajew, Michael Karow, Robert A. Granat and Ralph E. Byers. Their work appears in journals such as SIAM Journal on Matrix Analysis and Applications, SIAM Journal on Scientific Computing, BIT Numerical Mathematics, Linear Algebra and its Applications and Numerical Algorithms.

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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