Michael D. Perlman
- Statistics and Probability top 0.2%
- Artificial Intelligence top 1%
- Management Science and Operations Research top 1%
- Molecular Biology
- Computational Theory and Mathematics top 2%
- Co-authors
- Steen A. AnderssonDavid MadiganLeon Jay GleserAllan R. SampsonS. James PressMathias DrtonMorris L. EatonLang Wu
- Topics
- Bayesian Modeling and Causal Inference (21 papers)Advanced Statistical Methods and Models (19 papers)Statistical Methods and Bayesian Inference (17 papers)
- Cited by
- Statistics and ProbabilityManagement Science and Operations ResearchArtificial Intelligence
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Statistical AssociationProceedings of the IEEE
- Partner nations
- United StatesCanadaDenmark
In The Last Decade
Michael D. Perlman
96 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 184
- Statistics and Probability 1.2k
- Artificial Intelligence 940
- Management Science and Operations Research 407
- Molecular Biology 365
- Computational Theory and Mathematics 229
Countries citing papers authored by Michael D. Perlman
This map shows the geographic impact of Michael D. Perlman'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 Michael D. Perlman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael D. Perlman more than expected).
Fields of papers citing papers by Michael D. Perlman
This network shows the impact of papers produced by Michael D. Perlman. 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 Michael D. Perlman. The network helps show where Michael D. Perlman may publish in the future.
Co-authorship network of co-authors of Michael D. Perlman
This figure shows the co-authorship network connecting the top 25 collaborators of Michael D. Perlman. A scholar is included among the top collaborators of Michael D. Perlman 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 Michael D. Perlman. Michael D. Perlman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | A SINful Approach to Gaussian Graphical Model Selection | 7 |
| 8 | 19 | |
| 9 | 1 | |
| 10 | 19 | |
| 11 | 78 | |
| 12 | 7 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 17 | |
| 16 | 10 | |
| 17 | 47 | |
| 18 | 5 | |
| 19 | 2 | |
| 20 | 7 |
About Michael D. Perlman
Michael D. Perlman is a scholar working on Statistics and Probability, Discrete Mathematics and Combinatorics and Applied Mathematics, having authored 105 papers that have together received 2.8k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (21 papers), Advanced Statistical Methods and Models (19 papers) and Statistical Methods and Bayesian Inference (17 papers). The work is most often cited by research in Statistics and Probability (1.2k citations), Management Science and Operations Research (407 citations) and Artificial Intelligence (940 citations). Michael D. Perlman has collaborated with scholars based in United States, Canada and Denmark. Frequent co-authors include Steen A. Andersson, David Madigan, Leon Jay Gleser, Allan R. Sampson, S. James Press, Mathias Drton, Morris L. Eaton, Lang Wu, Somesh Das Gupta and James A. Koziol. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Statistical Association and Proceedings of the IEEE.
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.