James G. Booth
- Statistics and Probability top 1%
- Statistical Methods and Bayesian Inference 3
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- Face recognition and analysis 7
- Generative Adversarial Networks and Image Synthesis 2
- Face and Expression Recognition 2
- Computational Mechanics top 5%
- 3D Shape Modeling and Analysis 7
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- Bayesian Methods and Mixture Models 8
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- Bioinformatics and Genomic Networks 3
- Gene expression and cancer classification 3
- Co-authors
- Peter H. WestfallS. Stanley YoungStefanos ZafeiriouAnastasios RoussosDavid DunawayAllan PonniahJames P. HobertEpameinondas Antonakos
- Cited by
- Statistics and ProbabilityComputer Vision and Pattern RecognitionComputer Graphics and Computer-Aided Design
- Journals
- Journal of the American Statistical Association (3 papers)Bioinformatics (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)
- Partner nations
- United StatesUnited KingdomAustralia
In The Last Decade
James G. Booth
20 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 169
- Statistics and Probability 354
- Computer Vision and Pattern Recognition 553
- Computer Graphics and Computer-Aided Design 47
- Computational Mechanics 243
- Management Science and Operations Research 146
Countries citing papers authored by James G. Booth
This map shows the geographic impact of James G. Booth'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 G. Booth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James G. Booth more than expected).
Fields of papers citing papers by James G. Booth
This network shows the impact of papers produced by James G. Booth. 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 G. Booth. The network helps show where James G. Booth may publish in the future.
Co-authorship network
The 25 scholars most cited alongside James G. Booth, 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 | 2019 | 1 | |
| 2 | 2018 | 36 | |
| 3 | 2017 | 205 | |
| 4 | 2017 | 96 | |
| 5 | 2016 | 1 | |
| 6 | 2016 | 198 | |
| 7 | 2014 | 18 | |
| 8 | 2014 | 67 | |
| 9 | 2012 | 4 | |
| 10 | 2012 | 20 | |
| 11 | Closed form GLM cumulants and GLMM tting with a SQUAR-EM-LA 2 algorithm. | 2011 | 1 |
| 12 | 2008 | 4 | |
| 13 | 2007 | 2 | |
| 14 | 2001 | 17 | |
| 15 | 1998 | 85 | |
| 16 | 1997 | 2 | |
| 17 | 1995 | 12 | |
| 18 | Resampling-Based Multiple Testing.breakdown → | 1994 | 687 |
| 19 | 1993 | 11 | |
| 20 | 1990 | 41 |
About James G. Booth
James G. Booth is a scholar working on Statistics and Probability, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 20 papers that have together received 1.5k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (8 papers), Face recognition and analysis (7 papers), 3D Shape Modeling and Analysis (7 papers), Statistical Methods and Bayesian Inference (3 papers), Bioinformatics and Genomic Networks (3 papers), Gene expression and cancer classification (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Face and Expression Recognition (2 papers). The work is most often cited by research in Statistics and Probability (354 citations), Computer Vision and Pattern Recognition (553 citations) and Computer Graphics and Computer-Aided Design (47 citations). James G. Booth has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Peter H. Westfall, S. Stanley Young, Stefanos Zafeiriou, Anastasios Roussos, David Dunaway, Allan Ponniah, James P. Hobert, Epameinondas Antonakos, Ronald W. Butler and Yannis Panagakis. Their work appears in journals such as Journal of the American Statistical Association, Bioinformatics and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.