Welcome to ZhuSuan

ZhuSuan is a python probabilistic programming library for Bayesian deep learning, which conjoins the complimentary advantages of Bayesian methods and deep learning. ZhuSuan is built upon Tensorflow. Unlike existing deep learning libraries, which are mainly designed for deterministic neural networks and supervised tasks, ZhuSuan provides deep learning style primitives and algorithms for building probabilistic models and applying Bayesian inference. The supported inference algorithms include:

  • Variational inference with programmable variational posteriors, various objectives and advanced gradient estimators (SGVB, REINFORCE, VIMCO, etc.).
  • Importance sampling for learning and evaluating models, with programmable proposals.
  • Hamiltonian Monte Carlo (HMC) with parallel chains, and optional automatic parameter tuning.

Installation

ZhuSuan is still under development. Before the first stable release (1.0), please clone the GitHub repository and run

pip install .

in the main directory. This will install ZhuSuan and its dependencies automatically. ZhuSuan also requires Tensorflow version 1.0 or later. Because users should choose whether to install the cpu or gpu version of Tensorflow, we do not include it in the dependencies. See Installing Tensorflow.

If you are developing ZhuSuan, you may want to install in an “editable” or “develop” mode. Please refer to the Contribution section in README.

After installation, open your python console and type:

>>> import zhusuan as zs

If no error occurs, you’ve successfully installed ZhuSuan.

Indices and tables