Zlatko Drmač

1.8k total citations
41 papers, 1.1k citations indexed

About

Zlatko Drmač is a scholar working on Computational Theory and Mathematics, Numerical Analysis and Statistical and Nonlinear Physics. According to data from OpenAlex, Zlatko Drmač has authored 41 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computational Theory and Mathematics, 12 papers in Numerical Analysis and 11 papers in Statistical and Nonlinear Physics. Recurrent topics in Zlatko Drmač's work include Matrix Theory and Algorithms (25 papers), Model Reduction and Neural Networks (11 papers) and Numerical Methods and Algorithms (9 papers). Zlatko Drmač is often cited by papers focused on Matrix Theory and Algorithms (25 papers), Model Reduction and Neural Networks (11 papers) and Numerical Methods and Algorithms (9 papers). Zlatko Drmač collaborates with scholars based in Croatia, United States and Germany. Zlatko Drmač's co-authors include Elizabeth R. Jessup, Michael W. Berry, Krešimir Veselić, Vjeran Hari, Ivan Slapničar, Stanley C. Eisenstat, James Demmel, Ming Gu, Matjaž Omladič and Peter Arbenz and has published in prestigious journals such as IEEE Transactions on Automatic Control, Scientific Reports and Computer Physics Communications.

In The Last Decade

Zlatko Drmač

38 papers receiving 890 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zlatko Drmač Croatia 16 515 251 247 144 141 41 1.1k
Elizabeth R. Jessup United States 14 343 0.7× 128 0.5× 277 1.1× 286 2.0× 188 1.3× 53 1.1k
Gregorio Quintana‐Ortí Spain 20 376 0.7× 143 0.6× 182 0.7× 430 3.0× 77 0.5× 63 1.1k
Vincent Lefèvre France 10 777 1.5× 108 0.4× 139 0.6× 67 0.5× 141 1.0× 32 1.1k
Alexander Barvinok United States 20 632 1.2× 230 0.9× 289 1.2× 107 0.7× 17 0.1× 63 1.5k
Shin’ichi Oishi Japan 15 784 1.5× 173 0.7× 48 0.2× 158 1.1× 104 0.7× 132 1.2k
Laura Grigori France 14 408 0.8× 85 0.3× 179 0.7× 239 1.7× 31 0.2× 75 823
Sanzheng Qiao Canada 16 401 0.8× 150 0.6× 170 0.7× 69 0.5× 14 0.1× 62 824
George A. Gravvanis Greece 14 399 0.8× 123 0.5× 57 0.2× 192 1.3× 135 1.0× 121 827
Marko D. Petković Serbia 21 391 0.8× 288 1.1× 278 1.1× 55 0.4× 19 0.1× 96 1.7k
Roger G. Grimes United States 14 834 1.6× 337 1.3× 99 0.4× 303 2.1× 29 0.2× 28 1.4k

Countries citing papers authored by Zlatko Drmač

Since Specialization
Citations

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

Fields of papers citing papers by Zlatko Drmač

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zlatko Drmač

This figure shows the co-authorship network connecting the top 25 collaborators of Zlatko Drmač. A scholar is included among the top collaborators of Zlatko Drmač 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 Zlatko Drmač. Zlatko Drmač 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.
Beattie, Christopher, et al.. (2024). IRKA Is a Riemannian Gradient Descent Method. IEEE Transactions on Automatic Control. 70(5). 2979–2991.
2.
Drmač, Zlatko. (2024). A LAPACK Implementation of the Dynamic Mode Decomposition. ACM Transactions on Mathematical Software. 50(1). 1–32. 1 indexed citations
3.
Drmač, Zlatko. (2024). Hermitian Dynamic Mode Decomposition - Numerical Analysis and Software Solution. ACM Transactions on Mathematical Software. 50(1). 1–23. 3 indexed citations
4.
Mezić, Igor, et al.. (2024). A Koopman operator-based prediction algorithm and its application to COVID-19 pandemic and influenza cases. Scientific Reports. 14(1). 5788–5788. 7 indexed citations
5.
Nikšić, Tamara, et al.. (2022). Chebyshev kernel polynomial method for efficient calculation of the quasiparticle random phase approximation response function. Computer Physics Communications. 280. 108477–108477. 4 indexed citations
6.
Drmač, Zlatko, et al.. (2022). An Algorithm for the Complete Solution of the Quartic Eigenvalue Problem. ACM Transactions on Mathematical Software. 48(1). 1–34. 1 indexed citations
7.
Drmač, Zlatko, Igor Mezić, & Ryan Mohr. (2021). Identification of Nonlinear Systems Using the Infinitesimal Generator of the Koopman Semigroup—A Numerical Implementation of the Mauroy–Goncalves Method. Mathematics. 9(17). 2075–2075. 5 indexed citations
8.
Mohr, Ryan, et al.. (2020). Predicting the Critical Number of Layers for Hierarchical Support Vector Regression. Entropy. 23(1). 37–37. 3 indexed citations
9.
Drmač, Zlatko. (2015). SVD of Hankel matrices in Vandermonde-Cauchy product form. ETNA - Electronic Transactions on Numerical Analysis. 44. 593–623. 3 indexed citations
10.
Drmač, Zlatko, et al.. (2012). A contribution to the theory and practice of the block Kogbetliantz method for computing the SVD. BIT Numerical Mathematics. 52(4). 827–849. 7 indexed citations
11.
Drmač, Zlatko, et al.. (2005). Proceedings of the Conference on Applied Mathematics and Scientific Computing. CERN Document Server (European Organization for Nuclear Research). 30 indexed citations
12.
Barlow, Jesse L., et al.. (2004). A new stable bidiagonal reduction algorithm. Linear Algebra and its Applications. 397. 35–84. 19 indexed citations
13.
Drmač, Zlatko & Elizabeth R. Jessup. (2001). On Accurate Quotient Singular Value Computation in Floating-Point Arithmetic. SIAM Journal on Matrix Analysis and Applications. 22(3). 853–873. 3 indexed citations
14.
Drmač, Zlatko & Krešimir Veselić. (2000). Approximate eigenvectors as preconditioner. Linear Algebra and its Applications. 309(1-3). 191–215. 4 indexed citations
15.
Demmel, James, Ming Gu, Stanley C. Eisenstat, et al.. (1999). Computing the singular value decomposition with high relative accuracy. Linear Algebra and its Applications. 299(1-3). 21–80. 131 indexed citations
16.
Drmač, Zlatko. (1999). A posteriori computation of the singular vectors in a preconditioned Jacobi SVD algorithm. IMA Journal of Numerical Analysis. 19(2). 191–213. 35 indexed citations
17.
Drmač, Zlatko & Vjeran Hari. (1997). Relative Residual Bounds For The Eigenvalues of a Hermitian Semidefinite Matrix. SIAM Journal on Matrix Analysis and Applications. 18(1). 21–29. 11 indexed citations
18.
Drmač, Zlatko. (1997). Implementation of Jacobi Rotations for Accurate Singular Value Computation in Floating Point Arithmetic. SIAM Journal on Scientific Computing. 18(4). 1200–1222. 31 indexed citations
19.
Drmač, Zlatko. (1996). On relative residual bounds for the eigenvalues of a Hermitian matrix. Linear Algebra and its Applications. 244. 155–163. 13 indexed citations
20.
Drmač, Zlatko, Matjaž Omladič, & Krešimir Veselić. (1994). On the Perturbation of the Cholesky Factorization. SIAM Journal on Matrix Analysis and Applications. 15(4). 1319–1332. 23 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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