Peter Grünwald

4.7k citations
98 papers · 1.8k · h-index 21

Impact in

Papers in

    • Bayesian Modeling and Causal Inference 19
    • Machine Learning and Algorithms 18
    • Bayesian Methods and Mixture Models 9
    • Statistical Methods in Clinical Trials 13
    • Statistical Methods and Inference 12

Peter Grünwald

91 papers receiving 1.6k citations

Peers

Peter Grünwald
Comparison fields: 5 of 155
  • Statistics and Probability 329
  • General Decision Sciences 70
  • Artificial Intelligence 923
  • Management Science and Operations Research 262
  • Signal Processing 134
Replace Marco Zaffalon with:
Marco Zaffalon Switzerland
Terrence L. Fine United States
Serafı́n Moral Spain
Francis Edward Su United States
Jonas Peters Germany
Michael D. Perlman United States
Dominik Janzing Germany
John Steele United States
Max Chickering United States
John Hawkes United Kingdom
Peter Grünwald relative to Marco Zaffalon Switzerland Marco Zaffalon's profile →
Citations per field
00.5×2.6×
Marco Zaffalon · 1×
Citations per year

Countries citing papers authored by Peter Grünwald

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Peter Grünwald Line = papers co-authored together Peter Grünwald links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 98 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Advances in Minimum Description Length: Theory and Applications
2005276
2 2004256
3 2000112
4 2007102
5 200580
6 200662
7
The Minimum Description Length Principle and Reasoning under Uncertainty
199857
8 202145
9 200544
10 200341
11
Comparing Predictive Inference Methods for Discrete Domains
199738
12 200337
13 201237
14 200034
15 198934
16 202333
17 200927
18 202024
19 200724
20
Fast Rates for General Unbounded Loss Functions: From ERM to Generalized Bayes
202023

About Peter Grünwald

Peter Grünwald is a scholar working on Artificial Intelligence, Statistics and Probability, Management Science and Operations Research, Molecular Biology and Statistical and Nonlinear Physics, having authored 98 papers that have together received 1.8k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (19 papers), Machine Learning and Algorithms (18 papers), Statistical Methods in Clinical Trials (13 papers), Statistical Methods and Inference (12 papers), Advanced Bandit Algorithms Research (12 papers), Statistical Mechanics and Entropy (9 papers), Bayesian Methods and Mixture Models (9 papers) and Advanced Statistical Process Monitoring (8 papers). The work is most often cited by research in Statistics and Probability (329 citations), General Decision Sciences (70 citations), Artificial Intelligence (923 citations), Management Science and Operations Research (262 citations) and Signal Processing (134 citations). Peter Grünwald has collaborated with scholars based in Netherlands, United States and Germany. Frequent co-authors include A. P. Dawid, In Jae Myung, Mark A. Pitt, Petri Myllymäki, Kirsi Tirri, Joseph Y. Halpern, Steven de Rooij, Paul Vitányi, Wouter M. Koolen and Tim van Erven. Their work appears in journals such as Journal of Mathematical Psychology, Journal of the Royal Statistical Society Series B (Statistical Methodology), International Journal of Approximate Reasoning, Machine Learning and Die Naturwissenschaften.

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.

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