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A first-order probabilistic programming language in Julia

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JFOPPL (Ongoing Project)

A simple first-order probabilistic programming language in Julia. This PPL will support the following inference algorithms:

  • Importance Sampling
  • Metropolis Hastings
  • Metropolis within Gibbs
  • Hamiltonian Monte Carlo
  • Varitational Inference

The implementations were done mainly following Frank Wood's Graduate Course on Probabilistic Programming and the texts on design and implementation of probabilistic programming languages: Intro to Prob Prog and DIPPL.

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A first-order probabilistic programming language in Julia

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