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Practical Probabilistic Programming by Avi Pfeffer

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Chapter 10. Factored inference algorithms

This chapter covers

  • The basics of factored inference, definition of factors, and operations on factors
  • The variable elimination algorithm
  • The belief propagation algorithm

Now that you understand the basic rules of probabilistic inference, you’ll spend the next two chapters learning about some of the inference algorithms used in probabilistic programming. This will give you better insight into which algorithm works best for a particular problem and how to design a model sympathetic to that algorithm.

There are two main types of inference algorithms:

  • Factored algorithms work by operating on data structures called factors that capture the probabilistic model being reasoned about.
  • Sampling algorithms ...

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