Bayesian models of cognition

Bayesian models of cognition

Cached

Download Links

[cocosci.berkeley.edu]

by Thomas L. Griffiths , Charles Kemp , Joshua B. Tenenbaum

Citations:

11 - 0 self

BibTeX

@MISC{Griffiths_bayesianmodels,
    author = {Thomas L. Griffiths and Charles Kemp and Joshua B. Tenenbaum},
    title = {Bayesian models of cognition},
    year = {}
}

Bookmark

OpenURL

Abstract

For over 200 years, philosophers and mathematicians have been using probability theory to describe human cognition. While the theory of probabilities was first developed as a means of analyzing games of chance, it quickly took on a larger and deeper significance as a formal account of how rational agents should reason in situations of uncertainty

Citations

5664	Probabilistic Reasoning in Intelligent Systems - Pearl - 1988
3011	Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images - Geman - 1984
2959	Artificial Intelligence: a Modern Approach - Russell, Norvig - 1995
1484	D: Pattern Classification - Duda, Hart, et al.
1369	Latent Dirichlet allocation - Blei, Andrew, et al.
887	Bayesian Data Analysis - Gelman, Carlin, et al. - 2004
787	Field Theory - Wit, Smith - 1986
766	Causality: Models, reasoning, and inference - Pearl - 2001
764	S.: A solution to plato’s problem: The latent semantic analysis theory of acquisition, induction and representation of knowledge. Psychological Review 104 - Landauer, Dumais - 1997
759	Information Theory, Inference and Learning Algorithms - Mackay - 2003
717	Bayes factors - Kass, Raftery - 1995
710	A tutorial on learning with Bayesian networks - Heckerman - 1995
545	Probabilistic latent semantic indexing - Hofmann - 1999
521	Foundations of statistical natural language processing - Manning, Schütze - 1999
496	Statistical Language Learning - Charniak - 1993
477	Vision - Marr - 1982
449	Probabilistic inference using markov chain monte carlo methods - Neal - 1971
426	D.: Markov chain Monte Carlo in practice - Gilks, Richardson, et al. - 1996
384	Causation, prediction and search - Spirtes, Glymour, et al. - 1993
372	Finding scientific topics - Griffiths, Steyvers - 2004
364	A learning algorithm for Boltzmann machines - Ackley, Hinton - 1985
312	The adaptive character of thought - Anderson - 1990
312	M.M.: Context theory of classification learning - Medin, Schaffer - 1978
299	Attention, similarity, and the identificationcategorization relationship - Nosofsky - 1986
281	Ronquist F: MRBAYES: Bayesian inference of phylogenetic trees - JP
245	Markov chain sampling methods for Dirichlet process mixture models - Neal - 2000
239	Markov Chains - Norris - 1996
211	Conceptual Change in Childhood - Carey - 1985
194	CM: Pattern recognition and machine learning - Bishop
184	Retrieval time from semantic memory - Collins, Quillian - 1969
160	Connectionist learning of belief networks - Neal - 1992
159	Producing High-dimensional Semantic Spaces from Lexical Co-occurrence - Lund, Burgess - 1996
156	Being Bayesian about network structure. a Bayesian approach to structure discovery in Bayesian networks - Friedman, Koller
147	A spreading activation theory of semantic processing - Collins, Loftus - 1975
135	From covariation to causation: A causal power theory. Psychological Review, 104, 367-405. inference and causal learning 69 - Cheng - 1997
127	Hierarchical topic models and the nested chinese restaurant process - Blei, Griffiths, et al. - 2003
122	Infinite latent feature models and the Indian buffet process (Technical report - Griffiths, Ghahramani - 2005
120	Concepts and induction - Smith - 1989
115	Pattern recognition and categorization - Reed - 1972
103	Bayesian color constancy - Brainard, Freeman - 1997
99	Words, thoughts, and theories - Gopnik, Meltzoff - 1997
89	Integrating topics and syntax - Griffiths, Steyvers, et al. - 2005
84	Expectation-propagation for the generative aspect model - Minka, Lafferty - 2002
69	The University of South Florida Word Association, Rhyme, and Word Fragment Norms. Available at: http://www.usf.edu/FreeAssociation/ [retrieved March 9 - Nelson, McEvoy, et al. - 1998
60	The mind’s arrows: Bayes nets and graphical causal models in psychology - Glymour - 2001
58	Inferring causal networks from observations and interventions - Steyvers, Tenenbaum, et al. - 2003
56	Structure and strength in causal induction - Griffiths, Tenenbaum - 2005
56	AJ: Mathematical Statistics and Data Analysis. 2nd edition - Rice - 1995
55	Applying occam's razor in modeling cognition: a Bayesian approach - Myung, Pitt - 1997
48	A probabilistic approach to semantic representation. Paper presented at the - Griffiths, Steyvers - 2004