Lars Eldén

3.5k total citations
77 papers, 2.4k citations indexed

About

Lars Eldén is a scholar working on Computational Theory and Mathematics, Mathematical Physics and Applied Mathematics. According to data from OpenAlex, Lars Eldén has authored 77 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Computational Theory and Mathematics, 30 papers in Mathematical Physics and 22 papers in Applied Mathematics. Recurrent topics in Lars Eldén's work include Numerical methods in inverse problems (29 papers), Matrix Theory and Algorithms (24 papers) and Statistical and numerical algorithms (17 papers). Lars Eldén is often cited by papers focused on Numerical methods in inverse problems (29 papers), Matrix Theory and Algorithms (24 papers) and Statistical and numerical algorithms (17 papers). Lars Eldén collaborates with scholars based in Sweden, United States and Iran. Lars Eldén's co-authors include Berkant Savas, Fredrik Berntsson, Teresa Regińska, Haesun Park, Valeria Simoncini, Thomas I. Seidman, Xiaoli Feng, Patricia K. Lamm, Rasmus Bro and Åke Björck and has published in prestigious journals such as Mathematics of Computation, Pattern Recognition and SIAM Journal on Numerical Analysis.

In The Last Decade

Lars Eldén

72 papers receiving 2.2k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lars Eldén Sweden	26	939	832	585	455	432	77	2.4k
Moody T. Chu United States	27	359 0.4×	1.4k 1.7×	426 0.7×	135 0.3×	214 0.5×	97	2.6k
Albert Cohen France	30	386 0.4×	669 0.8×	1.9k 3.2×	230 0.5×	968 2.2×	88	3.5k
Raymond H. Chan Hong Kong	35	617 0.7×	1.4k 1.7×	1.4k 2.5×	230 0.5×	1.7k 4.0×	127	4.2k
Stefano Serra‐Capizzano Italy	37	572 0.6×	2.5k 3.0×	1.2k 2.0×	428 0.9×	341 0.8×	252	4.0k
James G. Nagy United States	26	729 0.8×	368 0.4×	905 1.5×	68 0.1×	1.1k 2.5×	107	2.5k
Raymond H. Chan Hong Kong	25	345 0.4×	646 0.8×	1.1k 1.9×	134 0.3×	1.9k 4.4×	75	3.5k
M. Zuhair Nashed United States	23	605 0.6×	813 1.0×	305 0.5×	174 0.4×	371 0.9×	104	2.2k
Bertrand Mercier France	11	594 0.6×	1.4k 1.6×	1.9k 3.3×	369 0.8×	541 1.3×	23	3.4k
Fuzhen Zhang United States	26	195 0.2×	1.5k 1.8×	323 0.6×	137 0.3×	277 0.6×	104	4.4k
Ming‐Jun Lai United States	25	293 0.3×	291 0.3×	2.0k 3.4×	253 0.6×	730 1.7×	92	2.9k

Countries citing papers authored by Lars Eldén

Since Specialization

Citations

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

Fields of papers citing papers by Lars Eldén

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lars Eldén

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

All Works

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20 of 20 papers shown

Eldén, Lars, et al.. (2022). Spectral partitioning of large and sparse 3‐tensors using low‐rank tensor approximation. Numerical Linear Algebra with Applications. 29(5). 1 indexed citations

Eldén, Lars, et al.. (2022). A Krylov-Schur-like method for computing the best rank-(r1,r2,r3) approximation of large and sparse tensors. Numerical Algorithms. 91(3). 1315–1347. 2 indexed citations

Eldén, Lars. (2019). Matrix Methods in Data Mining and Pattern Recognition, Second Edition. Society for Industrial and Applied Mathematics eBooks. 4 indexed citations

Eldén, Lars, et al.. (2018). Solving bilinear tensor least squares problems and application to Hammerstein identification. Numerical Linear Algebra with Applications. 26(2). 3 indexed citations

Rezghi, Mansoor & Lars Eldén. (2011). Diagonalization of tensors with circulant structure. Linear Algebra and its Applications. 435(3). 422–447. 22 indexed citations

Savas, Berkant & Lars Eldén. (2011). Krylov-type methods for tensor computations I. Linear Algebra and its Applications. 438(2). 891–918. 25 indexed citations

Merkel, Magnus, et al.. (2010). Computing Word Senses by Semantic Mirroring and Spectral Graph Partitioning. KTH Publication Database DiVA (KTH Royal Institute of Technology). 103–107. 2 indexed citations

Eldén, Lars. (2007). Matrix Methods in Data Mining and Pattern Recognition (Fundamentals of Algorithms). Society for Industrial and Applied Mathematics eBooks. 20 indexed citations

Eldén, Lars. (2007). Matrix Methods in Data Mining and Pattern Recognition. Society for Industrial and Applied Mathematics eBooks. 215 indexed citations

10.

Savas, Berkant & Lars Eldén. (2006). Handwritten digit classification using higher order singular value decomposition. Pattern Recognition. 40(3). 993–1003. 124 indexed citations

11.

Eldén, Lars & Berkant Savas. (2005). The maximum likelihood estimate in reduced‐rank regression. Numerical Linear Algebra with Applications. 12(8). 731–741. 5 indexed citations

12.

Eldén, Lars, et al.. (2004). Introduction to Numerical Computation. 3 indexed citations

13.

Lundström, Eva & Lars Eldén. (2002). Adaptive Eigenvalue Computations Using Newton's Method on the Grassmann Manifold. SIAM Journal on Matrix Analysis and Applications. 23(3). 819–839. 26 indexed citations

14.

Park, H., Sabine Van Huffel, & Lars Eldén. (2002). Fast algorithms for exponential data modeling. iv. IV/25–IV/28. 3 indexed citations

15.

Park, Haesun & Lars Eldén. (2002). Fast and accurate Toeplitz matrix triangulation for linear prediction. 8. 343–351.

16.

Regińska, Teresa & Lars Eldén. (1997). Solving the sideways heat equation by a wavelet - Galerkin method. Inverse Problems. 13(4). 1093–1106. 53 indexed citations

17.

Eldén, Lars, et al.. (1996). Fast computation of the principal singular vectors of Toeplitz matrices arising in exponential data modelling. Signal Processing. 50(1-2). 151–164. 9 indexed citations

18.

Park, Haesun & Lars Eldén. (1995). Downdating the Rank-Revealing URV Decomposition. SIAM Journal on Matrix Analysis and Applications. 16(1). 138–155. 22 indexed citations

19.

Eldén, Lars. (1988). Hyperbolic approximations for a Cauchy problem for the heat equation. Inverse Problems. 4(1). 59–70. 30 indexed citations

20.

Eldén, Lars. (1987). Approximations for a Cauchy problem for the heat equation. Inverse Problems. 3(2). 263–273. 61 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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