TreePPL documentation

If you are new to universal probabilistic programming and TreePPL, we recommend beginning by going through our introductory tutorial.

The TreePPL documentation consists of:

• Installing TreePPL, with instructions on how to install TreePPL,
• Python interface, documenting the Python interface,
• Jupyter interface, describing how to work with TreePPL in Jupyter notebooks,
• R interface, documenting the R interface,
• Tutorials, in which the user learns by doing something meaningful, towards some achievable goal,
• Language overview, which contains a basic language description,
• Distributions, describing available distributions and related information,
• Inference methods, describing available inference techniques,
• Model library, which contains model examples that can be used as templates,
• Troubleshooting, describing solutions to problems you may encounter when installing or running TreePPL,
• Contribute to TreePPL development, with instructions for installing the command-line version and for contributing to the TreePPL development effort,
• How to cite, with information on how to cite TreePPL.