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Probabilistic Numerics in Python.

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Probabilistic Numerics in Python

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probabilistic numerics 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.

pip install probnum

Alternatively, you can install the package from source.

pip install 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.

Package Development

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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