Stan
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Pyro | 7,975 |  | 18 | 42 | 4 days ago | 30 | March 24, 2022 | 238 | apache-2.0 | Python |
| Deep universal probabilistic programming with Python and PyTorch | ||||||||||
| Pymc | 7,603 |  | 143 | 95 | 10 hours ago | 36 | March 15, 2022 | 198 | other | Python |
| Bayesian Modeling in Python | ||||||||||
| Stan | 2,414 | 4 hours ago | 166 | bsd-3-clause | C++ | |||||
| Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details. | ||||||||||
| Zhusuan | 2,139 | 8 months ago | 11 | mit | Python | |||||
| A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow | ||||||||||
| Causalnex | 1,876 |  | 2 | 6 days ago | 16 | November 11, 2021 | 20 | other | Python | |
| A Python library that helps data scientists to infer causation rather than observing correlation. | ||||||||||
| Pytorch Bayesiancnn | 1,181 | 2 months ago | 15 | mit | Python | |||||
| Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch. | ||||||||||
| Bambi | 905 | 3 | 6 days ago | 21 | June 06, 2022 | 73 | mit | Python | ||
| BAyesian Model-Building Interface (Bambi) in Python. | ||||||||||
| Bda_py_demos | 851 | a year ago | gpl-3.0 | Jupyter Notebook | ||||||
| Bayesian Data Analysis demos for Python | ||||||||||
| Bayespy | 666 | 12 days ago | 5 | March 20, 2021 | 68 | mit | Python | |||
| Bayesian Python: Bayesian inference tools for Python | ||||||||||
| Bayesian Stats Modelling Tutorial | 601 | a year ago | 14 | mit | Jupyter Notebook | |||||
| How to do Bayesian statistical modelling using numpy and PyMC3 | ||||||||||
Stan is a C++ package providing
- full Bayesian inference using the No-U-Turn sampler (NUTS), a variant of Hamiltonian Monte Carlo (HMC),
- approximate Bayesian inference using automatic differentiation variational inference (ADVI), and
- penalized maximum likelihood estimation (MLE) using L-BFGS optimization.
It is built on top of the Stan Math library, which provides
- a full first- and higher-order automatic differentiation library based on C++ template overloads, and
- a supporting fully-templated matrix, linear algebra, and probability special function library.
There are interfaces available in R, Python, MATLAB, Julia, Stata, Mathematica, and for the command line.
Home Page
Stan's home page, with links to everything you'll need to use Stan is:
Interfaces
There are separate repositories in the stan-dev GitHub organization for the interfaces, higher-level libraries and lower-level libraries.
Source Repository
Stan's source-code repository is hosted here on GitHub.
Licensing
The Stan math library, core Stan code, and CmdStan are licensed under new BSD. RStan and PyStan are licensed under GPLv3, with other interfaces having other open-source licenses.
Note that the Stan math library depends on the Intel TBB library which is licensed under the Apache 2.0 license. This dependency implies an additional restriction as compared to the new BSD lincense alone. The Apache 2.0 license is incompatible with GPL-2 licensed code if distributed as a unitary binary. You may refer to the Licensing page on the Stan wiki.
