David H. Bailey

187 papers receiving 4.6k citations

David H. Bailey's Hit Papers

Enhancing reproducibility for computational methods 2016 · 259 citations
2590+11+23Years since publication100200300400

Peers

David H. Bailey
Comparison fields: 5 of 151
  • Hardware and Architecture 1.3k
  • Algebra and Number Theory 535
  • Theoretical Computer Science 133
  • Discrete Mathematics and Combinatorics 266
  • Computational Theory and Mathematics 1.2k
Replace Richard P. Brent with:
Richard P. Brent Australia
Martin Davis United States
Andrew Odlyzko United States
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Countries citing papers authored by David H. Bailey

Since Specialization
Citations

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

Fields of papers citing papers by David H. Bailey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David H. Bailey. 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 David H. Bailey. The network helps show where David H. Bailey may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 205 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The NAS parallel benchmarks---summary and preliminary results
Hit paper breakdown →
1991435
2
Enhancing reproducibility for computational methods
Hit paper breakdown →
2016259
3 2006254
4 2013198
5 2003194
6 1995167
7 1997166
8 2002152
9 2004117
10 2014115
11 1993108
12 2012105
13 1993105
14 2004103
15 2000102
16 2012102
17 1994101
18 200885
19 198965
20 201457

About David H. Bailey

David H. Bailey is a scholar working on Computational Theory and Mathematics, Hardware and Architecture, Artificial Intelligence, Algebra and Number Theory and Computer Networks and Communications, having authored 205 papers that have together received 5.0k indexed citations. Recurring topics across this work include Numerical Methods and Algorithms (39 papers), Parallel Computing and Optimization Techniques (36 papers), Advanced Mathematical Identities (25 papers), Analytic Number Theory Research (21 papers), Distributed and Parallel Computing Systems (18 papers), Advanced Combinatorial Mathematics (13 papers), Algorithms and Data Compression (12 papers) and Financial Markets and Investment Strategies (12 papers). The work is most often cited by research in Hardware and Architecture (1.3k citations), Algebra and Number Theory (535 citations), Theoretical Computer Science (133 citations), Discrete Mathematics and Combinatorics (266 citations) and Computational Theory and Mathematics (1.2k citations). David H. Bailey has collaborated with scholars based in United States, Australia and Canada. Frequent co-authors include Jonathan M. Borwein, Marcos López de Prado, Peter Borwein, Roland Girgensohn, Richard E. Crandall, Horst D. Simon, Simon Plouffe, Leonardo Dagum, Eric Barszcz and Yozo Hida. Their work appears in journals such as Mathematics of Computation, Experimental Mathematics, Computing in Science & Engineering, ACM Transactions on Mathematical Software and Journal of Physics B Atomic Molecular and Optical Physics.

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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