Jay Myung

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Mark PittProfessor, Ohio State UniversityVerified email at osu.edu
Daniel R. CavagnaroCalifornia State University FullertonVerified email at fullerton.edu
Woojae KimHoward UniversityVerified email at howard.edu
Zhong-Lin LuNYU Shanghai and NYUVerified email at nyu.edu
Jerome BusemeyerIndiana UniversityVerified email at indiana.edu
Woo-Young (Young) AhnSeoul National UniversityVerified email at snu.ac.kr
Vijay BalasubramanianUniversity of PennsylvaniaVerified email at physics.upenn.edu
Maximiliano MontenegroResearcher, Universidad de La SerenaVerified email at userena.cl
Peter GrünwaldGroup Leader Machine Learning, CWI; Professor of Statistics, Leiden UniversityVerified email at cwi.nl
Cheongtag KimDepartment of Psychology, Seoul National UniversityVerified email at snu.ac.kr
Benji MaruyamaAir Force Research LaboratoryVerified email at us.af.mil
Nathaniel HainesData Scientist and Computational PsychologistVerified email at osu.edu
Brandon TurnerThe Ohio State UniversityVerified email at osu.edu
Janne V. KujalaUniversity of TurkuVerified email at utu.fi
Mark SteyversUniversity of California, IrvineVerified email at uci.edu
John OpferProfessor, Department of Psychology, The Ohio State UniversityVerified email at osu.edu
Theodore BeauchaineUniversity of Notre DameVerified email at nd.edu
Sridhar RamamoortiUniversity of DaytonVerified email at udayton.edu
Samuel M. McClureDepartment of Psychology, Arizona State UniversityVerified email at asu.edu
Ahmad Ehteshamul IslamUS Air Force Research LaboratoryVerified email at us.af.mil

Jay Myung

Professor, Department of Psychology, Ohio State University

Verified email at osu.edu - Homepage

computational cognition autonomous experimentation machine learning Bayesian optimization


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Tutorial on maximum likelihood estimation IJ Myung Journal of mathematical Psychology 47 (1), 90-100, 2003	2540	2003
The importance of complexity in model selection IJ Myung Journal of mathematical psychology 44 (1), 190-204, 2000	667	2000
Toward a method of selecting among computational models of cognition. MA Pitt, IJ Myung, S Zhang Psychological review 109 (3), 472, 2002	649	2002
When a good fit can be bad MA Pitt, IJ Myung Trends in cognitive sciences 6 (10), 421-425, 2002	564	2002
Applying Occam’s razor in modeling cognition: A Bayesian approach IJ Myung, MA Pitt Psychonomic bulletin & review 4, 79-95, 1997	535	1997
Advances in minimum description length: Theory and applications PD Grünwald, IJ Myung, MA Pitt MIT press, 2005	510	2005
An adaptive approach to human decision making: Learning theory, decision theory, and human performance. JR Busemeyer, IJ Myung Journal of Experimental Psychology: General 121 (2), 177, 1992	289	1992
Counting probability distributions: Differential geometry and model selection IJ Myung, V Balasubramanian, MA Pitt Proceedings of the National Academy of Sciences 97 (21), 11170-11175, 2000	240	2000
Adaptive design optimization: A mutual information-based approach to model discrimination in cognitive science DR Cavagnaro, JI Myung, MA Pitt, JV Kujala Neural computation 22 (4), 887-905, 2010	207	2010
Optimal experimental design for model discrimination. JI Myung, MA Pitt Psychological review 116 (3), 499, 2009	185	2009
Global model analysis by parameter space partitioning. MA Pitt, W Kim, DJ Navarro, JI Myung Psychological Review 113 (1), 57, 2006	184	2006
Toward an explanation of the power law artifact: Insights from response surface analysis IJ Myung, C Kim, MA Pitt Memory & cognition 28, 832-840, 2000	172	2000
Model selection by normalized maximum likelihood JI Myung, DJ Navarro, MA Pitt Journal of Mathematical Psychology 50 (2), 167-179, 2006	165	2006
A tutorial on adaptive design optimization JI Myung, DR Cavagnaro, MA Pitt Journal of mathematical psychology 57 (3-4), 53-67, 2013	157	2013
GUEST EDITORS'INTRODUCTION: special issue on model selection IJ Myung, MR Forster, MW Browne Journal of Mathematical Psychology 44 (1), 1-2, 2000	144	2000
Assessing the distinguishability of models and the informativeness of data DJ Navarro, MA Pitt, IJ Myung Cognitive psychology 49 (1), 47-84, 2004	120	2004
Model comparison methods JI Myung, MA Pitt Methods in enzymology 383, 351-366, 2004	106	2004
A Bayesian approach to testing decision making axioms JI Myung, G Karabatsos, GJ Iverson Journal of Mathematical Psychology 49 (3), 205-225, 2005	105	2005
Toward autonomous additive manufacturing: Bayesian optimization on a 3D printer JR Deneault, J Chang, J Myung, D Hooper, A Armstrong, M Pitt, ... MRS Bulletin 46, 566-575, 2021	95	2021
A hierarchical adaptive approach to optimal experimental design W Kim, MA Pitt, ZL Lu, M Steyvers, JI Myung Neural computation 26 (11), 2465-2492, 2014	90	2014

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