Language Evolution by Iterated Learning With Bayesian Agents (2007)

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by Thomas L. Griffiths , Michael L. Kalish
Citations:18 - 6 self

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4 Technical Introduction: A Primer on Probabilistic Inference – Thomas L. Griffiths, Alan Yuille - 2006
393 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
11 Bayesian models of cognition – Thomas L. Griffiths, Charles Kemp, Joshua B. Tenenbaum
375 The Infinite Hidden Markov Model – Matthew J. Beal, Zoubin Ghahramani, Carl E. Rasmussen - 2002
Just Enough Die-Level Test: Optimizing IC Test via Machine Learning and Decision Theory – Tony Fountain - 1998
Hidden Dynamic Models for Speech Processing Applications – Leo Jingyu Lee
7 Prior Information and Generalized Questions – Jörg C. Lemm - 1996
Irregular-Structure Tree Models for Image Interpretation – Sinisa Todorovic - 2005
8 Rational approximations to rational models: Alternative algorithms for category learning – Adam N. Sanborn, Thomas L. Griffiths, Daniel J. Navarro, Adam Sanborn
7 Machine Learning Based on Attribute Interactions – Aleks Jakulin - 2005
141 An Introduction to MCMC for Machine Learning – Christophe Andrieu - 2003
6 Exploiting parameter domain knowledge for learning in Bayesian networks – Radu Stefan Niculescu - 2005
101 Learning dynamic Bayesian networks – Zoubin Ghahramani - 1998
710 A tutorial on learning with Bayesian networks – David Heckerman - 1995
17 Latent Variable Models for Neural Data Analysis – Maneesh Sahani - 1999
19 Nonparametric Bayesian Models of Lexical Acquisition – Sharon J. Goldwater - 2007
Continuous-state Graphical Models for . . . – Leonid Sigal - 2008
48 Topics in semantic representation – Thomas L. Griffiths, Joshua B. Tenenbaum, Mark Steyvers - 2007
11 Intuitive theories as grammars for causal inference – Joshua B. Tenenbaum, Thomas L. Griffiths, Sourabh Niyogi - 2007