Peter Grünwald

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Petri MyllymakiProfessor of Computer Science, University of HelsinkiVerified email at helsinki.fi
Tim van ErvenAssociate professor at the University of Amsterdam, the NetherlandsVerified email at uva.nl
Wouter M. KoolenCentrum Wiskunde & Informatica; University of TwenteVerified email at cwi.nl
Teemu RoosProfessor at University of HelsinkiVerified email at helsinki.fi
Nishant A. MehtaAssistant Professor, University of VictoriaVerified email at uvic.ca
Jay MyungProfessor, Department of Psychology, Ohio State UniversityVerified email at osu.edu
Mark PittProfessor, Ohio State UniversityVerified email at osu.edu
Thijs van OmmenAssistant Professor at Utrecht UniversityVerified email at uu.nl
Paul VitanyiCWI and University of AmsterdamVerified email at cwi.nl
Wojciech KotlowskiPoznan University of TechnologyVerified email at cs.put.poznan.pl
Rianne de HeideAssistant professor, Mathematics department, Vrije Universiteit AmsterdamVerified email at vu.nl
Joseph HalpernProfessor of Computer Science, Cornell UniversityVerified email at cs.cornell.edu
Philip DawidEmeritus Professor of Statistics, University of CambridgeVerified email at statslab.cam.ac.uk
Judith ter SchureAmsterdam UMCVerified email at amsterdamumc.nl
Richard D. GillProfessor of Mathematical Statistics, Leiden UniversityVerified email at math.leidenuniv.nl
Eric-Jan WagenmakersUniversity of AmsterdamVerified email at uva.nl
Alexander LyUniversity of Amsterdam, Centrum Wiskunde & InformaticaVerified email at uva.nl
Robert C. WilliamsonUniversity of TübingenVerified email at uni-tuebingen.de
Mark D. ReidAppleVerified email at reid.name
Wim van DamMicrosoftVerified email at microsoft.com

Peter Grünwald

Group Leader Machine Learning, CWI; Professor of Statistics, Leiden University

Verified email at cwi.nl - Homepage

machine learning statistics information theory foundations of probability statistics and the law


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
The minimum description length principle PD Grünwald The MIT Press, 2007	1704	2007
A tutorial introduction to the minimum description length principle P Grunwald Advances in Minimum Description Length - Theory and Methods, 2005	560*	2005
Game theory, maximum entropy, minimum discrepancy and robust Bayesian decision theory PD Grünwald, AP Dawid the Annals of Statistics 32 (4), 1367-1433, 2004	502	2004
Advances in Minimum Description Length: Theory and Applications PD Grünwald, J Myung, MA Pitt Advances in Minimum Description Length: Theory and Applications, 2005	445	2005
Model selection based on minimum description length P Grünwald Journal of mathematical psychology 44 (1), 133-152, 2000	204	2000
Shannon information and Kolmogorov complexity P Grunwald, P Vitányi arXiv preprint cs/0410002, 2004	191	2004
Inconsistency of Bayesian inference for misspecified linear models, and a proposal for repairing it P Grünwald, T Van Ommen Bayesian Analysis 12 (4), 1069-1103, 2017	184	2017
Follow the leader if you can, hedge if you must S de Rooij, T Van Erven, PD Grünwald, WM Koolen Journal of Machine Learning Research (JMLR) 15, 1281-1315, 2013	171	2013
The minimum description length principle and reasoning under uncertainty PD Grünwald Ph.D. thesis, University of Amsterdam, 1998	156	1998
On discriminative Bayesian network classifiers and logistic regression T Roos, H Wettig, P Grünwald, P Myllymäki, H Tirri Machine Learning 59 (3), 267-296, 2005	153	2005
A minimum description length approach to grammar inference P Grünwald International joint conference on artificial intelligence, 203-216, 1995	139	1995
Kolmogorov complexity and information theory. With an interpretation in terms of questions and answers PD Grünwald, PMB Vitányi Journal of Logic, Language and Information 12 (4), 497-529, 2003	124	2003
Accumulative prediction error and the selection of time series models EJ Wagenmakers, P Grünwald, M Steyvers Journal of Mathematical Psychology 50 (2), 149-166, 2006	115	2006
The safe Bayesian P Grünwald International Conference on Algorithmic Learning Theory, 169-183, 2012	106	2012
Updating probabilities P Grünwald, JY Halpern J. Artif. Intell. Res.(JAIR) 19, 243-278, 2003	88	2003
Catching up faster by switching sooner: a predictive approach to adaptive estimation with an application to the AIC–BIC dilemma T Erven, P Grünwald, S De Rooij Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2012	86	2012
Suboptimal behavior of Bayes and MDL in classification under misspecification P Grünwald, J Langford Machine Learning 66 (2), 119-149, 2007	86*	2007
The statistical strength of nonlocality proofs W Van Dam, RD Gill, PD Grunwald IEEE transactions on information theory 51 (8), 2812-2835, 2005	85	2005
Safe testing P Grünwald, R de Heide, WM Koolen arXiv preprint arxiv:1906.07801, 2020	76	2020
Fast rates in statistical and online learning T Van Erven, P Grunwald, NA Mehta, M Reid, R Williamson Journal of Machine Learning Research 16, 1793-1861, 2015	74	2015

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