John T. Ormerod
Impact in
- Statistics and Probability top 1%
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Advanced Statistical Methods and Models
- Artificial Intelligence top 5%
- Bayesian Methods and Mixture Models
- Gaussian Processes and Bayesian Inference
Papers in
-
- Statistical Methods and Inference 19
- Statistical Methods and Bayesian Inference 17
-
- Bayesian Methods and Mixture Models 19
- Gaussian Processes and Bayesian Inference 10
- Co-authors
- M. P. Wand (18 shared papers)Jean Yang (11 shared papers)Pengyi Yang (5 shared papers)Simone A. Padoan (2 shared papers)R. Frühwirth (2 shared papers)Samuel Müller (4 shared papers)Chong You (5 shared papers)Christel Faes (2 shared papers)
- Journals
- Journal of Computational and Graphical Statistics (5 papers)Computational Statistics & Data Analysis (4 papers)Bioinformatics (3 papers)Statistics and Computing (3 papers)Electronic Journal of Statistics (3 papers)
- Partner nations
- AustraliaUnited StatesChina
In The Last Decade
John T. Ormerod
48 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 125
- Statistics and Probability 511
- Artificial Intelligence 471
- Biophysics 59
- Ecological Modeling 29
- Statistics, Probability and Uncertainty 36
Countries citing papers authored by John T. Ormerod
This map shows the geographic impact of John T. Ormerod'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 John T. Ormerod with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John T. Ormerod more than expected).
Fields of papers citing papers by John T. Ormerod
This network shows the impact of papers produced by John T. Ormerod. 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 John T. Ormerod. The network helps show where John T. Ormerod may publish in the future.
Co-authors
The 25 scholars most cited alongside John T. Ormerod, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 239 | |
| 2 | 2008 | 135 | |
| 3 | 2019 | 117 | |
| 4 | 2011 | 96 | |
| 5 | 2011 | 57 | |
| 6 | 2016 | 52 | |
| 7 | 2011 | 51 | |
| 8 | 2018 | 45 | |
| 9 | 2014 | 30 | |
| 10 | 2017 | 30 | |
| 11 | 2011 | 29 | |
| 12 | 2022 | 28 | |
| 13 | 2019 | 28 | |
| 14 | Theory of Gaussian variational approximation for a Poisson mixed model | 2011 | 23 |
| 15 | 2014 | 21 | |
| 16 | 2013 | 19 | |
| 17 | 2016 | 18 | |
| 18 | 2015 | 16 | |
| 19 | 2016 | 12 | |
| 20 | 2013 | 11 |
About John T. Ormerod
John T. Ormerod is a scholar working on Statistics and Probability, Artificial Intelligence, Molecular Biology, Computational Mechanics and Control and Systems Engineering, having authored 50 papers that have together received 1.2k indexed citations. Recurring topics across this work include Statistical Methods and Inference (19 papers), Bayesian Methods and Mixture Models (19 papers), Statistical Methods and Bayesian Inference (17 papers), Gaussian Processes and Bayesian Inference (10 papers), Gene expression and cancer classification (8 papers), Single-cell and spatial transcriptomics (4 papers), Bioinformatics and Genomic Networks (4 papers) and Control Systems and Identification (3 papers). The work is most often cited by research in Statistics and Probability (511 citations), Artificial Intelligence (471 citations), Biophysics (59 citations), Ecological Modeling (29 citations) and Statistics, Probability and Uncertainty (36 citations). John T. Ormerod has collaborated with scholars based in Australia, United States and China. Frequent co-authors include M. P. Wand, Jean Yang, Pengyi Yang, Simone A. Padoan, R. Frühwirth, Samuel Müller, Chong You, Christel Faes, Yingxin Lin and Shila Ghazanfar. Their work appears in journals such as Journal of Computational and Graphical Statistics, Computational Statistics & Data Analysis, Bioinformatics, Statistics and Computing and Electronic Journal of Statistics.
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.