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Causal Induction Causal Induction
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Statistical Models of Language Statistical Models of Language
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Cultural Evolution and Iterated Learning Cultural Evolution and Iterated Learning

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Foundations
Foundations
Rational Process Models
Griffiths, T. L., Lieder, F., & Goodman, N. D. (in press). Rational use of cognitive resources: Levels of analysis between the computational and the algorithmic. Topics in Cognitive Science. (pdf)
Foundations
Griffiths, T. L., Tenenbaum, J. B., & Kemp, C. (2012). Bayesian inference. In K. J. Holyoak & R. G. Morrison, (Eds.) Oxford Handbook of Thinking and Reasoning. Oxford: Oxford University Press. (book)
Foundations
Griffiths, T. L., Chater, N., Norris, D., & Pouget, A. (2012). How the Bayesians got their beliefs (and what those beliefs actually are). Psychological Bulletin, 138, 415-422. (doi)
Foundations
Rational Process Models
Griffiths, T. L., Vul, E., & Sanborn, A. N. (2012). Bridging levels of analysis for probabilistic models of cognition. Current Directions in Psychological Science, 21(4), 263-268. (doi)
Foundations
Griffiths, T. L., Austerweil, J. L., & Berthiaume, V. G. (2012). Comparing the inductive biases of simple neural networks and Bayesian models. Proceedings of the 34th Annual Conference of the Cognitive Science Society. (pdf)
Foundations
Cognitive Development
Perfors, A., Tenenbaum, J.B., Griffiths, T. L., & Xu, F. (2011). A tutorial introduction to Bayesian models of cognitive development. Cognition, 120, 302-321. (pdf)
Foundations
Cognitive Development
Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011) How to grow a mind: Statistics, structure, and abstraction. Science, 331, 1279-1285. (doi)
Foundations
Griffiths, T. L., Chater, N., Kemp, C., Perfors, A., & Tenenbaum, J. B. (2010). Probabilistic models of cognition: Exploring representations and inductive biases. Trends in Cognitive Sciences, 14, 357-364. (pdf)
Foundations
Griffiths, T. L. (2010). Bayesian models as tools for exploring inductive biases. In M. Banich & D. Caccamise (Eds.) Generalization of knowledge: Multidisciplinary perspectives. New York: Psychology Press. (book)
Foundations
Griffiths, T.L. (2009). Connecting human and machine learning via probabilistic models of cognition. InterSpeech 2009. (pdf)
Foundations
Griffiths, T. L., & Yuille, A. (2008). A primer on probabilistic inference. In M. Oaksford and N. Chater (Eds.). The probabilistic mind: Prospects for rational models of cognition. Oxford: Oxford University Press. (manuscript pdf)
Foundations
Griffiths, T. L., Kemp, C., & Tenenbaum, J. B. (2008). Bayesian models of cognition. In Ron Sun (ed.), The Cambridge handbook of computational cognitive modeling. Cambridge University Press. (manuscript pdf)
Foundations
Griffiths, T. L., & Yuille, A. (2006). A primer on probabilistic inference. Trends in Cognitive Sciences. Supplement to special issue on Probabilistic Models of Cognition (volume 10, issue 7). (pdf)
Foundations
Causal Induction
Tenenbaum, J. B., Griffiths, T. L., & Kemp, C. (2006). Theory-based Bayesian models of inductive learning and reasoning. Trends in Cognitive Science, 10, 309-318. (pdf)
Foundations
Probabilistic Reasoning
Griffiths, T. L., & Tenenbaum, J. B. (2006). Statistics and the Bayesian mind. Significance, 3, 130-133. (pdf)

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