G. A. Watson

2.6k citations
99 papers · 1.7k · h-index 21

Impact in

Papers in

G. A. Watson

96 papers receiving 1.5k citations

Peers

G. A. Watson
Comparison fields: 5 of 126
  • Numerical Analysis 532
  • Computational Mathematics 43
  • Computational Theory and Mathematics 581
  • Statistics and Probability 180
  • Applied Mathematics 232
Replace J. M. Varah with:
J. M. Varah Canada
L.M. Bregman United States
James M. Ortega United States
Daniel Gabay France
Ronald Cools Belgium
J.M. Peña Spain
Klaus Höllig Germany
L. Mirsky United Kingdom
M. Zuhair Nashed United States
Allan Pinkus Israel
G. A. Watson relative to J. M. Varah Canada J. M. Varah's profile →
Citations per field
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J. M. Varah · 1×
Citations per year

Countries citing papers authored by G. A. Watson

Since Specialization
Citations

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

Fields of papers citing papers by G. A. Watson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G. A. Watson. 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 G. A. Watson. The network helps show where G. A. Watson may publish in the future.

Co-authors

The 20 scholars most cited alongside G. A. Watson, 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 G. A. Watson Line = papers co-authored together G. A. Watson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 99 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1992240
2
Approximation theory and numerical methods
1980151
3 200579
4 199778
5 196969
6 198566
7
Computational methods for matrix Eigenproblems
197364
8 197848
9 200346
10 196736
11 199832
12 198029
13 199728
14 198128
15 199325
16 197924
17 198722
18 199322
19 197522
20 198521

About G. A. Watson

G. A. Watson is a scholar working on Computational Theory and Mathematics, Numerical Analysis, Applied Mathematics, Statistics and Probability and Computer Vision and Pattern Recognition, having authored 99 papers that have together received 1.7k indexed citations. Recurring topics across this work include Matrix Theory and Algorithms (23 papers), Advanced Optimization Algorithms Research (20 papers), Statistical and numerical algorithms (17 papers), Approximation Theory and Sequence Spaces (14 papers), Image and Object Detection Techniques (11 papers), Mathematical Approximation and Integration (9 papers), Control Systems and Identification (9 papers) and Optimization and Variational Analysis (8 papers). The work is most often cited by research in Numerical Analysis (532 citations), Computational Mathematics (43 citations), Computational Theory and Mathematics (581 citations), Statistics and Probability (180 citations) and Applied Mathematics (232 citations). G. A. Watson has collaborated with scholars based in United Kingdom, Australia and China. Frequent co-authors include M. R. Osborne, Iain Duff, Chong Li, I. D. Coope, A. R. Gourlay, R. Fletcher, David F. Griffiths, Ka Fai Cedric Yiu, Chong Li and Keith J. Topping. Their work appears in journals such as Journal of Approximation Theory, IMA Journal of Numerical Analysis, BIT Numerical Mathematics, Numerical Algorithms and SIAM Journal on Matrix Analysis and Applications.

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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