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Computational Cognitive Science Lab
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Resources

Research

  • Representative Papers:
    • Theory-based Bayesian models of inductive learning and reasoning
    • The discovery of structural form
    • Optimal predictions in everyday cognition
    • A global geometric framework for nonlinear dimensionality reduction
  • Tutorials:
    • Church Wiki:
      Probabilistic Models of Cognition Tutorial
    • Josh Tenenbaum and Tom Griffiths:
      Tutorial at the Annual Meeting of the Cognitive Science Society 2004 (ppt)
    • Tom Griffiths, Josh Tenenbaum, and Charles Kemp:
      Tutorial at the Annual Meeting of the Cognitive Science Society 2006 (ppt)
    • Tom Griffiths, Josh Tenenbaum, and Charles Kemp:
      Tutorial at the Annual Meeting of the Cognitive Science Society 2008 (pdf)
  • Videos & Slides:
    Graduate Summer School in Probabilistic Models of Cognition
  • Griffiths, Kemp, and Tenenbaum:
    Bayesian models of cognition.
    The Cambridge handbook of computational cognitive modeling.
  • Tom Griffiths:
    A reading list on Bayesian methods
  • Trends in Cognitive Sciences:
    Special issue: Probabilistic models of cognition

Collaborators

  • Early Childhood Cognition Lab
  • Learning and Intelligent Systems Lab (LIS)
  • Saxe Lab
  • TedLab: The Language Lab
  • Kanwisher Lab
  • Computational Visual Cognition Laboratory
  • UC Berkeley Computational Cognitive Science Lab
  • William T. Freeman
  • Charles Kemp
  • Patrick Shafto
  • Pedro Domingos
  • Jeffrey Mark Siskind
  • Michael Littman
  • Antonio Torralba
  • David Barner
  • Fei Xu

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