M. Tibbits
Impact in
- Statistics and Probability top 10%
- Markov Chains and Monte Carlo Methods
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
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- Privacy-Preserving Technologies in Data
- Bayesian Methods and Mixture Models
- Cryptography and Data Security
- Gaussian Processes and Bayesian Inference
Papers in
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- Bayesian Methods and Mixture Models 2
- Privacy-Preserving Technologies in Data 1
- Cryptography and Data Security 1
- Gaussian Processes and Bayesian Inference 1
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- Markov Chains and Monte Carlo Methods 2
- Statistical Methods and Inference 1
- Co-authors
- Murali Haran (2 shared papers)John Liechty (2 shared papers)Aleksandra Slavković (1 shared paper)Yuval Nardi (1 shared paper)J. W. C. McNabb (1 shared paper)A. L. Stuver (1 shared paper)T. Z. Summerscales (1 shared paper)P. J. Sutton (1 shared paper)
- Journals
- Classical and Quantum Gravity (1 paper)Journal of Computational and Graphical Statistics (1 paper)Statistics and Computing (1 paper)
- Partner nations
- United States
In The Last Decade
M. Tibbits
4 papers receiving 89 citations
Peers
Comparison fields: 5 of 49
- Statistics and Probability 27
- Artificial Intelligence 51
- Astronomy and Astrophysics 17
- Applied Microbiology and Biotechnology 1
- Computer Science Applications 3
Countries citing papers authored by M. Tibbits
This map shows the geographic impact of M. Tibbits'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 M. Tibbits with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Tibbits more than expected).
Fields of papers citing papers by M. Tibbits
This network shows the impact of papers produced by M. Tibbits. 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 M. Tibbits. The network helps show where M. Tibbits may publish in the future.
Co-authors
The 12 scholars most cited alongside M. Tibbits, 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 | 2013 | 29 | |
| 2 | 2007 | 29 | |
| 3 | 2010 | 19 | |
| 4 | 2004 | 18 | |
| 5 | Parallel markov chain Monte Carlo | 2011 | 0 |
About M. Tibbits
M. Tibbits is a scholar working on Artificial Intelligence, Statistics and Probability, Molecular Biology, Condensed Matter Physics and Astronomy and Astrophysics, having authored 5 papers that have together received 95 indexed citations. Recurring topics across this work include Markov Chains and Monte Carlo Methods (2 papers), Bayesian Methods and Mixture Models (2 papers), Privacy-Preserving Technologies in Data (1 paper), Metabolomics and Mass Spectrometry Studies (1 paper), Theoretical and Computational Physics (1 paper), Cryptography and Data Security (1 paper), Gaussian Processes and Bayesian Inference (1 paper) and Statistical Methods and Inference (1 paper). The work is most often cited by research in Statistics and Probability (27 citations), Artificial Intelligence (51 citations), Astronomy and Astrophysics (17 citations), Applied Microbiology and Biotechnology (1 citation) and Computer Science Applications (3 citations). M. Tibbits has collaborated with scholars based in United States. Frequent co-authors include Murali Haran, John Liechty, Aleksandra Slavković, Yuval Nardi, J. W. C. McNabb, A. L. Stuver, T. Z. Summerscales, P. J. Sutton, M. C. B. Ashley and E. Rotthoff. Their work appears in journals such as Classical and Quantum Gravity, Journal of Computational and Graphical Statistics and Statistics and Computing.
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.