blei-lab/edward

Edward is a Python library for probabilistic modeling, inference, and criticism. It enables black box inference for models with discrete and continuous latent variables, neural network parameterizations, and infinite dimensional parameter spaces. Edward serves as a fusion of three fields: Bayesian statistics and machine learning, deep learning, and probabilistic programming. You can find a tutorial here for getting started with Edward, as well as a tutorial here for how to use it for research. Edward is led by Dustin Tran with guidance by David Blei.