John K. Kruschke
John K. Kruschke
Provost Professor, Indiana University
Verified email at indiana.edu - Homepage
Title
Cited by
Cited by
Year
Doing Bayesian Data Analysis, Second Edition: A Tutorial with R, JAGS, and Stan
JK Kruschke
Academic Press, 2015
2490*2015
ALCOVE: An exemplar-based connectionist model of category learning.
JK Kruschke
Psychological review 99 (1), 22, 1992
21281992
Bayesian estimation supersedes the t test.
JK Kruschke
Journal of Experimental Psychology: General 142 (2), 573-603, 2013
9262013
Rules and exemplars in category learning.
MA Erickson, JK Kruschke
Journal of Experimental Psychology: General 127 (2), 107, 1998
7541998
The Bayesian new statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective
JK Kruschke, TM Liddell
Psychonomic Bulletin & Review, 2016
3882016
Combining exemplar-based category representations and connectionist learning rules.
RM Nosofsky, JK Kruschke, SC McKinley
Journal of Experimental Psychology: Learning, Memory, and Cognition 18 (2), 211, 1992
3861992
Toward a unified model of attention in associative learning
JK Kruschke
Journal of mathematical psychology 45 (6), 812-863, 2001
3532001
Bayesian assessment of null values via parameter estimation and model comparison
JK Kruschke
Perspectives on Psychological Science 6 (3), 299, 2011
3282011
The time has come: Bayesian methods for data analysis in the organizational sciences
JK Kruschke, H Aguinis, H Joo
Organizational Research Methods 15 (4), 722-752, 2012
2932012
A model of probabilistic category learning.
JK Kruschke, MK Johansen
Journal of Experimental Psychology: Learning, Memory, and Cognition 25 (5), 1083, 1999
2921999
What to believe: Bayesian methods for data analysis
JK Kruschke
Trends in cognitive sciences 14 (7), 293-300, 2010
2832010
Blocking and backward blocking involve learned inattention
JK Kruschke, NJ Blair
Psychonomic Bulletin & Review 7 (4), 636-645, 2000
2552000
Base rates in category learning.
JK Kruschke
Journal of Experimental Psychology: Learning, Memory, and Cognition 22 (1), 3, 1996
2411996
Attention in learning
JK Kruschke
Current Directions in Psychological Science 12 (5), 171-175, 2003
2102003
Eye gaze and individual differences consistent with learned attention in associative blocking and highlighting.
JK Kruschke, ES Kappenman, WP Hetrick
Journal of Experimental Psychology: Learning, Memory, and Cognition 31 (5), 830, 2005
2012005
Human category learning: Implications for backpropagation models
JK Kruschke
Connection Science 5 (1), 3-36, 1993
2001993
Bayesian data analysis
JK Kruschke
Wiley Interdisciplinary Reviews: Cognitive Science 1 (5), 658-676, 2010
1852010
Benefits of gain: Speeded learning and minimal hidden layers in back-propagation networks
JK Kruschke, JR Movellan
IEEE Transactions on systems, Man, and Cybernetics 21 (1), 273-280, 1991
1781991
Dimensional relevance shifts in category learning
JK Kruschke
Connection Science 8 (2), 225-248, 1996
1601996
Locally Bayesian learning with applications to retrospective revaluation and highlighting.
JK Kruschke
Psychological review 113 (4), 677, 2006
1502006
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