• ☰
  • Home
  • Introduction
  • Generative models
  • Conditioning
  • Causal and statistical dependence
  • Conditional dependence
  • Social cognition
  • Interlude - Bayesian data analysis
  • Interlude - Algorithms for inference
  • Rational process models
  • Learning as conditional inference
  • Learning with a language of thought
  • Hierarchical models
  • Occam's Razor
  • Mixture models
  • Learning (deep) continuous functions
  • Appendix - JavaScript basics
  • Appendix - Useful distributions

For further reading on Bayesian data analysis see:

• Lee & Wagenmakers (2013),
• Kruschke (2014),
• Gelman et al. (2014).

For an extended example of using these tools in WebPPL, see the Example: BDA for Tug of War.