John Stutz
Impact in
- Signal Processing top 2%
- Data Management and Algorithms
- Artificial Intelligence top 2%
- Advanced Clustering Algorithms Research
- Bayesian Modeling and Causal Inference
- Bayesian Methods and Mixture Models
Papers in
-
- Bayesian Methods and Mixture Models 3
- Imbalanced Data Classification Techniques 2
-
- Advanced Statistical Methods and Models 4
- Co-authors
- Peter Cheeseman (13 shared papers)Robin Hanson (4 shared papers)Matthew W. Self (5 shared papers)James G. Kelly (1 shared paper)Bob Kanefsky (2 shared papers)Richard Kraft (2 shared papers)Jeremy Frank (1 shared paper)J. Castle (2 shared papers)
- Journals
- Proceedings of the American Mathematical Society (1 paper)Journal of Artificial Intelligence Research (1 paper)Transactions of the American Mathematical Society (1 paper)Elsevier eBooks (1 paper)Knowledge Discovery and Data Mining (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
John Stutz
17 papers receiving 1.4k citations
John Stutz's Hit Papers
Peers
Comparison fields: 5 of 137
- Signal Processing 353
- Artificial Intelligence 946
- Information Systems 433
- Computer Vision and Pattern Recognition 324
- Media Technology 103
Countries citing papers authored by John Stutz
This map shows the geographic impact of John Stutz'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 Stutz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Stutz more than expected).
Fields of papers citing papers by John Stutz
This network shows the impact of papers produced by John Stutz. 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 Stutz. The network helps show where John Stutz may publish in the future.
Co-authors
The 17 scholars most cited alongside John Stutz, 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 | Bayesian classification (AutoClass): theory and results Hit paper breakdown → | 1996 | 787 |
| 2 | 1988 | 382 | |
| 3 | 1996 | 169 | |
| 4 | Bayesian classification theory | 1991 | 89 |
| 5 | 1997 | 73 | |
| 6 | 1996 | 38 | |
| 7 | 2009 | 38 | |
| 8 | Bayesian classification with correlation and inheritance | 1991 | 37 |
| 9 | Automatic classification of spectra from the Infrared Astronomical Satellite (IRAS) | 1989 | 22 |
| 10 | A Bayesian classification of the IRAS LRS Atlas | 1989 | 16 |
| 11 | 1972 | 10 | |
| 12 | 2005 | 8 | |
| 13 | An Improved Automatic Classification of a Landsat/TM Image from Kansas (FIFE) | 1994 | 7 |
| 14 | 2007 | 5 | |
| 15 | Subpixel Resolution from Multiple Images | 1994 | 4 |
| 16 | 2018 | 1 | |
| 17 | Automatic discovery of optimal classes | 1986 | 1 |
| 18 | 1976 | 0 | |
| 19 | Bayesian Classification Scheme | 1992 | 0 |
| 20 | 2017 | 0 |
About John Stutz
John Stutz is a scholar working on Artificial Intelligence, Statistics and Probability, Computer Vision and Pattern Recognition, Algebra and Number Theory and Computational Mechanics, having authored 20 papers that have together received 1.7k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (4 papers), Bayesian Methods and Mixture Models (3 papers), Risk and Safety Analysis (2 papers), Spectroscopy and Chemometric Analyses (2 papers), Imbalanced Data Classification Techniques (2 papers), Computer Graphics and Visualization Techniques (2 papers), Rings, Modules, and Algebras (1 paper) and Engineering Diagnostics and Reliability (1 paper). The work is most often cited by research in Signal Processing (353 citations), Artificial Intelligence (946 citations), Information Systems (433 citations), Computer Vision and Pattern Recognition (324 citations) and Media Technology (103 citations). John Stutz has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Peter Cheeseman, Robin Hanson, Matthew W. Self, James G. Kelly, Bob Kanefsky, Richard Kraft, Jeremy Frank, J. Castle, Nikunj C. Oza and J. H. Goebel. Their work appears in journals such as Proceedings of the American Mathematical Society, Journal of Artificial Intelligence Research, Transactions of the American Mathematical Society, Elsevier eBooks and Knowledge Discovery and Data Mining.
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.