Jim Kay
Impact in
- Statistics and Probability top 1%
- Statistical Methods and Inference
- Advanced Statistical Methods and Models
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
- Visual perception and processing mechanisms
- Functional Brain Connectivity Studies
Papers in
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- Neural Networks and Applications 12
- Bayesian Methods and Mixture Models 3
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- Neural dynamics and brain function 12
- Co-authors
- D. M. Titterington (10 shared papers)William A. Phillips (10 shared papers)Peter Hall (1 shared paper)Adam Thompson (4 shared papers)J. Aitchison (4 shared papers)J. C. Brown (1 shared paper)Frank Pollick (2 shared papers)Kathrin Heim (1 shared paper)
- Journals
- Network Computation in Neural Systems (4 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (3 papers)Biometrika (2 papers)Neural Computation (2 papers)Statistical Methods in Medical Research (2 papers)
- Partner nations
- United KingdomGermanyAustralia
In The Last Decade
Jim Kay
51 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 152
- Statistics and Probability 351
- Cognitive Neuroscience 513
- Computer Vision and Pattern Recognition 252
- Artificial Intelligence 342
- Statistics, Probability and Uncertainty 51
Countries citing papers authored by Jim Kay
This map shows the geographic impact of Jim Kay'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 Jim Kay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jim Kay more than expected).
Fields of papers citing papers by Jim Kay
This network shows the impact of papers produced by Jim Kay. 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 Jim Kay. The network helps show where Jim Kay may publish in the future.
Co-authors
The 25 scholars most cited alongside Jim Kay, 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 52 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1990 | 246 | |
| 2 | 1991 | 213 | |
| 3 | 2005 | 167 | |
| 4 | 2015 | 87 | |
| 5 | 1995 | 77 | |
| 6 | 1977 | 69 | |
| 7 | 1998 | 60 | |
| 8 | 2010 | 45 | |
| 9 | 2021 | 43 | |
| 10 | 1991 | 42 | |
| 11 | 1997 | 42 | |
| 12 | 1996 | 40 | |
| 13 | Statistics and neural networks: advances at the interface | 2000 | 38 |
| 14 | 1994 | 37 | |
| 15 | 2000 | 33 | |
| 16 | 2022 | 32 | |
| 17 | 1989 | 32 | |
| 18 | 1997 | 32 | |
| 19 | 1995 | 28 | |
| 20 | Possible solution of some essential zero problems in compositional data analysis | 2003 | 28 |
About Jim Kay
Jim Kay is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Statistics and Probability, Computer Vision and Pattern Recognition and Global and Planetary Change, having authored 52 papers that have together received 1.7k indexed citations. Recurring topics across this work include Neural Networks and Applications (12 papers), Neural dynamics and brain function (12 papers), Statistical Methods and Inference (10 papers), Image and Signal Denoising Methods (8 papers), Radioactive contamination and transfer (4 papers), Bayesian Methods and Mixture Models (3 papers), Statistical Methods and Bayesian Inference (3 papers) and Genetic and phenotypic traits in livestock (2 papers). The work is most often cited by research in Statistics and Probability (351 citations), Cognitive Neuroscience (513 citations), Computer Vision and Pattern Recognition (252 citations), Artificial Intelligence (342 citations) and Statistics, Probability and Uncertainty (51 citations). Jim Kay has collaborated with scholars based in United Kingdom, Germany and Australia. Frequent co-authors include D. M. Titterington, William A. Phillips, Peter Hall, Adam Thompson, J. Aitchison, J. C. Brown, Frank Pollick, Kathrin Heim, Rebecca Stringer and Darragh Smyth. Their work appears in journals such as Network Computation in Neural Systems, IEEE Transactions on Pattern Analysis and Machine Intelligence, Biometrika, Neural Computation and Statistical Methods in Medical Research.
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.