probabilistic numerics

Learn to Approximate. Approximate to Learn.

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Solve Numerical Problems

Solve problems from linear algebra, optimization, quadrature and differential equations using probabilistic inference.

Quantify Uncertainty in Computation

Quantify and propagate uncertainty from finite resources and stochastic input in computational pipelines.

Compose Custom Numerical Methods

Create problem-specific probabilistic numerical methods from predefined or your own custom components.


To get started install ProbNum using pip.
pip install probnum

Then in a Python session simply import ProbNum.

import probnum as pn
ProbNum is first and foremost a community project. It was originally conceived at the Chair for the Methods of Machine Learning at the University of Tübingen. ProbNum's core development team is supported by research grants of the European Research Council (ERC StG Action 757275 / PANAMA), the German Federal Ministry of Education and Research (BMBF) through both project ADIMEM (FKZ 01IS18052B) and the Tübingen AI Center (FKZ: 01IS18039A); by the German Research Union (DFG) through the DFG Cluster of Excellence “Machine Learning - New Perspectives for Science”, (EXC 2064/1, project number 390727645), and the Ministry of Science, Research and Arts of the State of Baden-Württemberg.