C. Ray Smith
- Statistics and Probability top 10%
- Artificial Intelligence top 10%
- Neural Networks and Applications 1
- Bayesian Modeling and Causal Inference 1
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- Image and Signal Denoising Methods 2
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- Statistical and numerical algorithms 1
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- Reservoir Engineering and Simulation Methods 1
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- Numerical methods in inverse problems 1
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- Control Systems and Identification 1
- Co-authors
- Gary J. EricksonDana Kelly
- Journals
- Kluwer Academic eBooks (1 paper)Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) (1 paper)CERN Document Server (European Organization for Nuclear Research) (4 papers)
- Partner nations
- United States
In The Last Decade
C. Ray Smith
7 papers receiving 491 citations
Peers
Comparison fields: 5 of 106
- Statistical and Nonlinear Physics 124
- Statistics, Probability and Uncertainty 68
- Structural Biology 6
- Statistics and Probability 30
- Artificial Intelligence 99
Countries citing papers authored by C. Ray Smith
This map shows the geographic impact of C. Ray Smith'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 C. Ray Smith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C. Ray Smith more than expected).
Fields of papers citing papers by C. Ray Smith
This network shows the impact of papers produced by C. Ray Smith. 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 C. Ray Smith. The network helps show where C. Ray Smith may publish in the future.
Co-authorship network
The 2 scholars most cited alongside C. Ray Smith, 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 | 2011 | 56 | |
| 2 | 1998 | 45 | |
| 3 | Maximum entropy and Bayesian methods : proceedings of the Eleventh International Workshop on Maximum Entropy and Bayesian Methods of Statistical Analysis, Seattle, 1991 | 1992 | 2 |
| 4 | 1991 | 5 | |
| 5 | 1988 | 205 | |
| 6 | 1987 | 26 | |
| 7 | 1985 | 205 |
About C. Ray Smith
C. Ray Smith is a scholar working on Mathematical Physics, Computer Vision and Pattern Recognition, Applied Mathematics, Ocean Engineering and Artificial Intelligence, having authored 7 papers that have together received 544 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (2 papers), Statistical and numerical algorithms (1 paper), Reservoir Engineering and Simulation Methods (1 paper), Neural Networks and Applications (1 paper), Bayesian Modeling and Causal Inference (1 paper), Numerical methods in inverse problems (1 paper) and Control Systems and Identification (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (124 citations), Statistics, Probability and Uncertainty (68 citations), Structural Biology (6 citations), Statistics and Probability (30 citations) and Artificial Intelligence (99 citations). C. Ray Smith has collaborated with scholars based in United States. Frequent co-authors include Gary J. Erickson and Dana Kelly. Their work appears in journals such as Kluwer Academic eBooks, Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)), CERN Document Server (European Organization for Nuclear Research) and Journal of the Royal Statistical Society Series D (The Statistician).
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.