Peter Grünwald
Impact in
- Statistics and Probability top 1%
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- General Decision Sciences top 5%
Papers in
-
- Machine Learning and Algorithms 23
- Bayesian Modeling and Causal Inference 21
- Bayesian Methods and Mixture Models 10
-
- Statistical Methods in Clinical Trials 13
- Statistical Methods and Inference 12
- Co-authors
- A. P. Dawid (2 shared papers)Mark A. Pitt (1 shared paper)In Jae Myung (1 shared paper)Steven de Rooij (10 shared papers)Petri Myllymäki (9 shared papers)Paul Vitányi (3 shared papers)Joseph Y. Halpern (3 shared papers)Wouter M. Koolen (11 shared papers)
- Journals
- Journal of Mathematical Psychology (5 papers)Journal of the Royal Statistical Society Series B (Statistical Methodology) (3 papers)Die Naturwissenschaften (2 papers)Machine Learning (2 papers)Proceedings of the National Academy of Sciences (2 papers)
- Partner nations
- NetherlandsGermanyUnited States
In The Last Decade
Peter Grünwald
110 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 163
- Statistics and Probability 406
- General Decision Sciences 78
- Artificial Intelligence 1.2k
- Management Science and Operations Research 309
- Signal Processing 188
Countries citing papers authored by Peter Grünwald
This map shows the geographic impact of Peter Grünwald'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 Peter Grünwald with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Grünwald more than expected).
Fields of papers citing papers by Peter Grünwald
This network shows the impact of papers produced by Peter Grünwald. 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 Peter Grünwald. The network helps show where Peter Grünwald may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Grünwald, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 122 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Advances in Minimum Description Length: Theory and Applications | 2005 | 324 |
| 2 | 2004 | 282 | |
| 3 | 2007 | 139 | |
| 4 | 2000 | 128 | |
| 5 | 2005 | 97 | |
| 6 | 2006 | 71 | |
| 7 | 1996 | 66 | |
| 8 | The Minimum Description Length Principle and Reasoning under Uncertainty | 1998 | 64 |
| 9 | 2021 | 53 | |
| 10 | 2003 | 47 | |
| 11 | 2005 | 46 | |
| 12 | Comparing Predictive Inference Methods for Discrete Domains | 1997 | 43 |
| 13 | 2000 | 41 | |
| 14 | 2003 | 41 | |
| 15 | 2012 | 40 | |
| 16 | 2012 | 40 | |
| 17 | 1989 | 36 | |
| 18 | 2023 | 35 | |
| 19 | 2007 | 30 | |
| 20 | 2005 | 29 |
About Peter Grünwald
Peter Grünwald is a scholar working on Artificial Intelligence, Statistics and Probability, Management Science and Operations Research, Computational Theory and Mathematics and Molecular Biology, having authored 122 papers that have together received 2.2k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (23 papers), Bayesian Modeling and Causal Inference (21 papers), Computability, Logic, AI Algorithms (13 papers), Statistical Methods in Clinical Trials (13 papers), Advanced Bandit Algorithms Research (13 papers), Statistical Methods and Inference (12 papers), Statistical Mechanics and Entropy (11 papers) and Bayesian Methods and Mixture Models (10 papers). The work is most often cited by research in Statistics and Probability (406 citations), General Decision Sciences (78 citations), Artificial Intelligence (1.2k citations), Management Science and Operations Research (309 citations) and Signal Processing (188 citations). Peter Grünwald has collaborated with scholars based in Netherlands, Germany and United States. Frequent co-authors include A. P. Dawid, Mark A. Pitt, In Jae Myung, Steven de Rooij, Petri Myllymäki, Paul Vitányi, Joseph Y. Halpern, Wouter M. Koolen, Tim van Erven and Teemu Roos. Their work appears in journals such as Journal of Mathematical Psychology, Journal of the Royal Statistical Society Series B (Statistical Methodology), Die Naturwissenschaften, Machine Learning and Proceedings of the National Academy of Sciences.
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.