J. F. Traub

7.5k total citations · 3 hit papers
87 papers, 4.9k citations indexed

About

J. F. Traub is a scholar working on Computational Theory and Mathematics, Numerical Analysis and Artificial Intelligence. According to data from OpenAlex, J. F. Traub has authored 87 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Computational Theory and Mathematics, 31 papers in Numerical Analysis and 14 papers in Artificial Intelligence. Recurrent topics in J. F. Traub's work include Matrix Theory and Algorithms (22 papers), Iterative Methods for Nonlinear Equations (21 papers) and Advanced Optimization Algorithms Research (18 papers). J. F. Traub is often cited by papers focused on Matrix Theory and Algorithms (22 papers), Iterative Methods for Nonlinear Equations (21 papers) and Advanced Optimization Algorithms Research (18 papers). J. F. Traub collaborates with scholars based in United States, Poland and Canada. J. F. Traub's co-authors include David M. Young, H. Woźniakowski, H. T. Kung, Michael Jenkins, Edward W. Packel, Spassimir H. Paskov, Warren S. Brown, Anargyros Papageorgiou, Y. Yemini and J. E. Dennis and has published in prestigious journals such as Nature, Science and Physics Today.

In The Last Decade

J. F. Traub

75 papers receiving 4.2k citations

Hit Papers

Iterative Methods for the Solution of Equations. 1967 2026 1986 2006 1967 1974 1980 500 1000 1.5k

Peers

J. F. Traub
Comparison fields: 5 of 143
  • Numerical Analysis 2.9k
  • Computational Theory and Mathematics 2.3k
  • Computational Mechanics 601
  • Artificial Intelligence 562
  • Modeling and Simulation 532
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Citations per field, relative to J. F. Traub
J. F. Traub · 1×
Citations per year, relative to J. F. Traub
J. F. Traub · 1×

Countries citing papers authored by J. F. Traub

Since Specialization
Citations

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

Fields of papers citing papers by J. F. Traub

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J. F. Traub. 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 J. F. Traub. The network helps show where J. F. Traub may publish in the future.

Co-authorship network of co-authors of J. F. Traub

This figure shows the co-authorship network connecting the top 25 collaborators of J. F. Traub. A scholar is included among the top collaborators of J. F. Traub 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 J. F. Traub. J. F. Traub 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
# Work Indexed citations
1 0
2 1
3 18
4 51
5
Recent progress in information-based complexity.
1
6 11
7
Annual review of computer science vol. 1, 1986
2
8 1
9 9
10 26
11 39
12
Algorithms and Complexity: New Directions and Recent Results
260
13
Parallel Algorithms and Parallel Comnputational Complexity.
1
14
Complexity of Sequential and Parallel Numerical Algorithms
78
15
Optimal Iterative Processes: Theorems and Conjectures.
3
16 14
17 178
18 29
19 6
20 2

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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