12 found
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  1.  17
    Rational Approximations to Rational Models: Alternative Algorithms for Category Learning.Adam N. Sanborn, Thomas L. Griffiths & Daniel J. Navarro - 2010 - Psychological Review 117 (4):1144-1167.
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  2.  5
    Bayesian Brains Without Probabilities.Adam N. Sanborn & Nick Chater - 2016 - Trends in Cognitive Sciences 20 (12):883-893.
  3.  12
    Reconciling Intuitive Physics and Newtonian Mechanics for Colliding Objects.Adam N. Sanborn, Vikash K. Mansinghka & Thomas L. Griffiths - 2013 - Psychological Review 120 (2):411-437.
  4. Belief Propagation and Locally Bayesian Learning.Adam N. Sanborn & Ricardo Silva - 2009 - In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society. pp. 31.
     
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  5.  13
    Categorization as Nonparametric Bayesian Density Estimation.Thomas L. Griffiths, Adam N. Sanborn, Kevin R. Canini & Daniel J. Navarro - 2008 - In Nick Chater & Mike Oaksford (eds.), The Probabilistic Mind: Prospects for Bayesian Cognitive Science. Oxford University Press.
  6. Categorization as Nonparametric Bayesian Density Estimation.Thomas L. Griffiths, Adam N. Sanborn, Kevin R. Canini & Navarro & J. Daniel - 2008 - In Nick Chater & Mike Oaksford (eds.), The Probabilistic Mind: Prospects for Bayesian Cognitive Science. Oxford University Press.
     
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  7. A Bayesian Framework for Modeling Intuitive Dynamics.Adam N. Sanborn, Vikash Mansinghka & Thomas L. Griffiths - 2009 - In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society.
     
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  8.  11
    Testing Bayesian and Heuristic Predictions of Mass Judgments of Colliding Objects.Adam N. Sanborn - 2014 - Frontiers in Psychology 5.
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  9.  7
    A Dilution Effect Without Dilution: When Missing Evidence, Not Non-Diagnostic Evidence, is Judged Inaccurately.Adam N. Sanborn, Takao Noguchi, James Tripp & Neil Stewart - 2020 - Cognition 196:104110.
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  10.  4
    The Bayesian Sampler: Generic Bayesian Inference Causes Incoherence in Human Probability Judgments.Jian-Qiao Zhu, Adam N. Sanborn & Nick Chater - 2020 - Psychological Review 127 (5):719-748.
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  11.  45
    Testing the Efficiency of Markov Chain Monte Carlo With People Using Facial Affect Categories.Jay B. Martin, Thomas L. Griffiths & Adam N. Sanborn - 2012 - Cognitive Science 36 (1):150-162.
    Exploring how people represent natural categories is a key step toward developing a better understanding of how people learn, form memories, and make decisions. Much research on categorization has focused on artificial categories that are created in the laboratory, since studying natural categories defined on high-dimensional stimuli such as images is methodologically challenging. Recent work has produced methods for identifying these representations from observed behavior, such as reverse correlation (RC). We compare RC against an alternative method for inferring the structure (...)
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  12.  10
    The Sampling Brain.Adam N. Sanborn & Nick Chater - 2017 - Trends in Cognitive Sciences 21 (7):492-493.
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