Theory-based causal induction (2003)

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by Thomas L. Griffiths , Joshua B. Tenenbaum
Venue:In
Citations:37 - 15 self

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Contents lists available at ScienceDirect Computational Biology and Chemistry – Nicole Davis A, Natasha Biddlecom A, David Hecht A, Gary B. Fogel B
13 Intuitive theories as grammars for causal inference – Joshua B. Tenenbaum, Thomas L. Griffiths, Sourabh Niyogi - 2007
579 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
1143 A solution to Plato’s problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge – Thomas K Landauer, Susan T. Dutnais - 1997
23 Bayesian models of cognition – Thomas L. Griffiths, Charles Kemp, Joshua B. Tenenbaum
753 Using Bayesian networks to analyze expression data – Nir Friedman, Michal Linial, Iftach Nachman - 2000
522 An integrated theory of the mind – John R. Anderson, Daniel Bothell, Michael D. Byrne, Scott Douglass, Christian Lebiere, Yulin Qin - 2004
872 A tutorial on learning with Bayesian networks – David Heckerman - 1995
924 Learning Bayesian networks: The combination of knowledge and statistical data – David Heckerman, David M. Chickering - 1995