Bayesian models of cognition

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by Thomas L. Griffiths , Charles Kemp , Joshua B. Tenenbaum
Citations:22 - 1 self

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5 Technical Introduction: A Primer on Probabilistic Inference – Thomas L. Griffiths, Alan Yuille - 2006
78 Topics in semantic representation – Thomas L. Griffiths, Mark Steyvers, Joshua B. Tenenbaum - 2007
12 Population Markov Chain Monte Carlo – Kathryn Blackmond Laskey, James Myers - 2003
564 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
13 Intuitive theories as grammars for causal inference – Joshua B. Tenenbaum, Thomas L. Griffiths, Sourabh Niyogi - 2007
53 The nested chinese restaurant process and bayesian inference of topic hierarchies – David M. Blei, Thomas L. Griffiths, Michael I. Jordan - 2007
Bayesian Modelling in Machine Learning: A Tutorial Review – Matthias Seeger - 2009
6 Bayesian Input Variable Selection Using Posterior Probabilities and Expected Utilities – Aki Vehtari, Jouko Lampinen - 2002
25 Language Evolution by Iterated Learning With Bayesian Agents – Thomas L. Griffiths , Michael L. Kalish - 2007
28 Modeling individual differences using Dirichlet processes – Daniel J. Navarro , Thomas L. Griffiths , Mark Steyvers , Michael D. Lee - 2006
1 Probabilistic Reasoning and Inference for Systems Biology – Vladislav Vyshemirsky - 2007
61 Probabilistic Reasoning for Complex Systems – Avrom J. Pfeffer - 2000
33 Theory-based causal induction – Thomas L. Griffiths, Joshua B. Tenenbaum - 2003
AND – David M. Blei, Thomas L. Griffiths, Michael, I. Jordan
36 Learning Probabilistic Networks – Paul J Krause - 1998
9 Exploiting parameter domain knowledge for learning in Bayesian networks – Radu Stefan Niculescu - 2005
Just Enough Die-Level Test: Optimizing IC Test via Machine Learning and Decision Theory – Tony Fountain - 1998
31 An Introduction to Graphical Models – Kevin P. Murphy - 2001
Bayesian Models of Inductive Learning – Thomas L. Griffiths (tom, Charles Kemp, Joshua B. Tenenbaum