Ross Kindermann
Impact in
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- Medical Image Segmentation Techniques
- Image Retrieval and Classification Techniques
- Advanced Image and Video Retrieval Techniques
- Image and Signal Denoising Methods
- Artificial Intelligence top 5%
- Bayesian Methods and Mixture Models
- Bayesian Modeling and Causal Inference
Papers in
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- Bayesian Methods and Mixture Models 3
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- Statistical Distribution Estimation and Applications 3
- Co-authors
- J. Laurie Snell (2 shared papers)Martin S. Levy (1 shared paper)V. N. LaRiccia (1 shared paper)
- Journals
- The Annals of Probability (1 paper)Journal of Mathematical Sociology (1 paper)Statistics & Probability Letters (1 paper)Communication in Statistics- Theory and Methods (2 papers)Contemporary mathematics - American Mathematical Society (1 paper)
- Partner nations
- United States
In The Last Decade
Ross Kindermann
6 papers receiving 773 citations
Ross Kindermann's Hit Papers
Peers
Comparison fields: 5 of 106
- Computer Vision and Pattern Recognition 219
- Artificial Intelligence 282
- Statistics and Probability 65
- Statistical and Nonlinear Physics 92
- Media Technology 56
Countries citing papers authored by Ross Kindermann
This map shows the geographic impact of Ross Kindermann'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 Ross Kindermann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ross Kindermann more than expected).
Fields of papers citing papers by Ross Kindermann
This network shows the impact of papers produced by Ross Kindermann. 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 Ross Kindermann. The network helps show where Ross Kindermann may publish in the future.
Co-authors
The 3 scholars most cited alongside Ross Kindermann, 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 | Markov Random Fields and Their Applications Hit paper breakdown → | 1980 | 803 |
| 2 | 1980 | 25 | |
| 3 | 1983 | 5 | |
| 4 | 1985 | 2 | |
| 5 | 1984 | 1 | |
| 6 | 1980 | 1 |
About Ross Kindermann
Ross Kindermann is a scholar working on Artificial Intelligence, Statistics and Probability, Mathematical Physics, Sociology and Political Science and Statistical and Nonlinear Physics, having authored 6 papers that have together received 837 indexed citations. Recurring topics across this work include Statistical Distribution Estimation and Applications (3 papers), Bayesian Methods and Mixture Models (3 papers), Stochastic processes and financial applications (1 paper), Hydrology and Drought Analysis (1 paper), Economic theories and models (1 paper), Complex Network Analysis Techniques (1 paper), Probability and Risk Models (1 paper) and Opinion Dynamics and Social Influence (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (219 citations), Artificial Intelligence (282 citations), Statistics and Probability (65 citations), Statistical and Nonlinear Physics (92 citations) and Media Technology (56 citations). Ross Kindermann has collaborated with scholars based in United States. Frequent co-authors include J. Laurie Snell, Martin S. Levy and V. N. LaRiccia. Their work appears in journals such as The Annals of Probability, Journal of Mathematical Sociology, Statistics & Probability Letters, Communication in Statistics- Theory and Methods and Contemporary mathematics - American Mathematical Society.
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.