Link

• ​An Introduction to Probabilistic Programming (2018)​

• ​pdatastructs - Simple probabilistic data structures.

• ​Gen - General-purpose probabilistic programming system with programmable inference.

• ​MIT Probabilistic Computing Project​

• ​End-User Probabilistic Programming paper by Microsoft Research​

• ​monad-bayes - Library for probabilistic programming in Haskell.

• ​Funsor - Functional tensors for probabilistic programming.

• ​Pyro - Deep universal probabilistic programming with Python and PyTorch.

• ​TensorFlow Probability - Library for probabilistic reasoning and statistical analysis in TensorFlow.

• ​Soss: Probabilistic Programming with Julia (2020)​

• ​NumPyro - Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

• ​Edward2 - Simple probabilistic programming language.

• ​MCX - Express & compile probabilistic programs for performant inference on CPU & GPU. Powered by JAX. (Intro)

• ​Soss - Julia library for probabilistic programming via source rewriting.

• ​Orbit - Python package for time series modeling and inference using Bayesian sampling methods for model estimation. (Docs)

• ​PyMC3 - Python package for Bayesian statistical modeling and Probabilistic Machine Learning focusing on advanced Markov chain Monte Carlo (MCMC) and variational inference (VI) algorithms.

• ​PyMC3 Resources​

• ​Ranked Programming - Ranked Programming Extension for Racket. Ranked programming is similar to probabilistic programming, except that the underlying uncertainty formalism is replaced with ranking theory.