Probabilistic Numerics in Python.
Probabilistic Numerics in Python
Probabilistic Numerics (PN) interprets classic numerical routines as inference procedures by taking a probabilistic viewpoint. This allows principled treatment of uncertainty arising from finite computational resources. The vision of probabilistic numerics is to provide well-calibrated probability measures over the output of a numerical routine, which then can be propagated along the chain of computation.
This repository aims to implement methods from PN in Python 3 and to provide a common interface for them. This is currently a work in progress, therefore interfaces are subject to change.
To get started install ProbNum using :code:
pip install probnum
Alternatively, you can install the package from source.
pip install git+https://github.com/probabilistic-numerics/probnum.git
Documentation and Examples
For tips on getting started and how to use this package please refer to the documentation. It contains a quickstart guide and Jupyter notebooks illustrating the basic usage of implemented probabilistic numerics routines.
This repository is currently under development and benefits from contribution to the code, examples or documentation. Please refer to the contribution guidelines before making a pull request.
A list of core contributors to ProbNum can be found here.
License and Contact
This work is released under the MIT License.
Please submit an issue on GitHub to report bugs or request changes.
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