James E. Gentle
- Statistics and Probability top 0.5%
- Advanced Statistical Methods and Models 8
- Fuzzy Systems and Optimization 5
- Statistical Distribution Estimation and Applications 3
- Artificial Intelligence top 2%
- Bayesian Methods and Mixture Models 3
- Neural Networks and Applications 3
-
- Control Systems and Identification 7
- Optimization and Mathematical Programming 3
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- Advanced Optimization Algorithms Research 4
- Co-authors
- Craig B. BorkowfL. KaufmanVirginia A. ClarkA. A. AfifiT. KrishnanGeoffrey J. McLachlanWilliam J. KennedyWolfgang Karl Härdle
- Journals
- Biometrics (7 papers)Technometrics (5 papers)Computational Statistics & Data Analysis (3 papers)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
James E. Gentle
58 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 214
- Statistics and Probability 522
- Statistics, Probability and Uncertainty 251
- Artificial Intelligence 703
- Management Science and Operations Research 260
- Computer Vision and Pattern Recognition 343
Countries citing papers authored by James E. Gentle
This map shows the geographic impact of James E. Gentle'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 James E. Gentle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James E. Gentle more than expected).
Fields of papers citing papers by James E. Gentle
This network shows the impact of papers produced by James E. Gentle. 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 James E. Gentle. The network helps show where James E. Gentle may publish in the future.
Co-authorship network
The 25 scholars most cited alongside James E. Gentle, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2017 | 16 | |
| 3 | 2017 | 0 | |
| 4 | 2016 | 3 | |
| 5 | 2010 | 4 | |
| 6 | Building Virtual Community In Computational Intelligence and Machine Learning | 2009 | 7 |
| 7 | 2008 | 6 | |
| 8 | 2007 | 2 | |
| 9 | 2004 | 149 | |
| 10 | Special Section: Teaching Computational Statistics | 2004 | 22 |
| 11 | 1997 | 20 | |
| 12 | 1991 | 3 | |
| 13 | 1991 | 263 | |
| 14 | 1990 | 7 | |
| 15 | 1982 | 1 | |
| 16 | 1982 | 1 | |
| 17 | 1981 | 14 | |
| 18 | 1977 | 55 | |
| 19 | 1977 | 2 | |
| 20 | 1975 | 0 |
About James E. Gentle
James E. Gentle is a scholar working on Statistics and Probability, Numerical Analysis, Control and Systems Engineering, Finance and Artificial Intelligence, having authored 65 papers that have together received 3.5k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (8 papers), Control Systems and Identification (7 papers), Fuzzy Systems and Optimization (5 papers), Advanced Optimization Algorithms Research (4 papers), Bayesian Methods and Mixture Models (3 papers), Statistical Distribution Estimation and Applications (3 papers), Neural Networks and Applications (3 papers) and Optimization and Mathematical Programming (3 papers). The work is most often cited by research in Statistics and Probability (522 citations), Statistics, Probability and Uncertainty (251 citations), Artificial Intelligence (703 citations), Management Science and Operations Research (260 citations) and Computer Vision and Pattern Recognition (343 citations). James E. Gentle has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Craig B. Borkowf, L. Kaufman, Virginia A. Clark, A. A. Afifi, T. Krishnan, Geoffrey J. McLachlan, William J. Kennedy, Wolfgang Karl Härdle, Yuichi Mori and D. J. G. Farlie. Their work appears in journals such as Biometrics, Technometrics, Computational Statistics & Data Analysis, Journal of the American Statistical Association and Statistics and Computing.
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.