Probabilistic inference

References

Brancher - A user-centered Python package for differentiable probabilistic inference
- https://brancher.org/
- https://github.com/AI-DI/Brancher
pymc3 - Probabilistic Programming in Python
- https://docs.pymc.io/
- PyMC3 - 简介和入门 https://blog.csdn.net/jackxu8/article/details/71080865
Bayesian Python: Bayesian inference tools for Python
- https://github.com/bayespy/bayespy
Pythonic Bayesian Belief Network Package, supporting creation of and exact inference on Bayesian Belief Networks specified as pure python functions.
- https://github.com/eBay/bayesian-belief-networks
Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference
在PyStan中应用贝叶斯回归
- https://www.toutiao.com/a6784058862472266254/
- https://pystan.readthedocs.io/en/latest/

Baysian tools

VIBES (http://vibes.sourceforge.net/) allows variational inference to be performed automatically on a Bayesian network. It is implemented in Java and released under revised BSD license.
Bayes Blocks (http://research.ics.aalto.fi/bayes/software/) is a C++/Python implementation of the variational building block framework. The framework allows easy learning of a wide variety of models using variational Bayesian learning. It is available as free software under the GNU General Public License.
Infer.NET (http://research.microsoft.com/infernet/) is a .NET framework for machine learning. It provides message-passing algorithms and statistical routines for performing Bayesian inference. It is partly closed source and licensed for non-commercial use only.
PyMC (https://github.com/pymc-devs/pymc) provides MCMC methods in Python. It is released under the Academic Free License.
OpenBUGS (http://www.openbugs.info) is a software package for performing Bayesian inference using Gibbs sampling. It is released under the GNU General Public License.
Dimple (http://dimple.probprog.org/) provides Gibbs sampling, belief propagation and a few other inference algorithms for Matlab and Java. It is released under the Apache License.
Stan (http://mc-stan.org/) provides inference using MCMC with an interface for R and Python. It is released under the New BSD License.
PBNT - Python Bayesian Network Toolbox (http://pbnt.berlios.de/) is Bayesian network library in Python supporting static networks with discrete variables. There was no information about the license.

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Probabilistic inference

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