Theodore Papamarkou
- Molecular Biology
- Artificial Intelligence
- Statistical and Nonlinear Physics
- Pulmonary and Respiratory Medicine
- Statistics and Probability top 10%
- Co-authors
- Mark GirolamiChris J. OatesA. J. LawranceEmőke-Ágnes HorvátJacob HinkleM. Todd YoungDavid E. WombleVioleta Rayon-Estrada
- Topics
- Gaussian Processes and Bayesian Inference (5 papers)Chaos control and synchronization (5 papers)Bayesian Methods and Mixture Models (3 papers)
- Partner nations
- United KingdomUnited StatesAustria
In The Last Decade
Theodore Papamarkou
23 papers receiving 246 citations
Peers
Comparison fields: 5 of 89
- Molecular Biology 95
- Artificial Intelligence 54
- Statistical and Nonlinear Physics 37
- Pulmonary and Respiratory Medicine 34
- Statistics and Probability 29
Countries citing papers authored by Theodore Papamarkou
This map shows the geographic impact of Theodore Papamarkou'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 Theodore Papamarkou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Theodore Papamarkou more than expected).
Fields of papers citing papers by Theodore Papamarkou
This network shows the impact of papers produced by Theodore Papamarkou. 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 Theodore Papamarkou. The network helps show where Theodore Papamarkou may publish in the future.
Co-authorship network of co-authors of Theodore Papamarkou
This figure shows the co-authorship network connecting the top 25 collaborators of Theodore Papamarkou. A scholar is included among the top collaborators of Theodore Papamarkou based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Theodore Papamarkou. Theodore Papamarkou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 8 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | Multiphase MCMC sampling for parameter inference in nonlinear ordinary differential equations | 2 |
| 11 | 24 | |
| 12 | 19 | |
| 13 | 15 | |
| 14 | 16 | |
| 15 | 34 | |
| 16 | 34 | |
| 17 | 4 | |
| 18 | 3 | |
| 19 | 1 | |
| 20 | 8 |
About Theodore Papamarkou
Theodore Papamarkou is a scholar working on Statistical and Nonlinear Physics, Statistics and Probability and Instrumentation, having authored 25 papers that have together received 255 indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (5 papers), Chaos control and synchronization (5 papers) and Bayesian Methods and Mixture Models (3 papers). The work is most often cited by research in Statistics and Probability (29 citations), Statistical and Nonlinear Physics (37 citations) and Modeling and Simulation (9 citations). Theodore Papamarkou has collaborated with scholars based in United Kingdom, United States and Austria. Frequent co-authors include Mark Girolami, Chris J. Oates, A. J. Lawrance, Emőke-Ágnes Horvát, Jacob Hinkle, M. Todd Young, David E. Womble, Violeta Rayon-Estrada, Dewi Harjanto and F. Nina Papavasiliou. Their work appears in journals such as Nucleic Acids Research, Nature Communications and Journal of the American Statistical Association.
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.