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ProbNum: Probabilistic Numerics in Python - MaRDI portal

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ProbNum: Probabilistic Numerics in Python

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Publication:6384766

arXiv2112.02100MaRDI QIDQ6384766

Author name not available (Why is that?)

Publication date: 3 December 2021

Abstract: Probabilistic numerical methods (PNMs) solve numerical problems via probabilistic inference. They have been developed for linear algebra, optimization, integration and differential equation simulation. PNMs naturally incorporate prior information about a problem and quantify uncertainty due to finite computational resources as well as stochastic input. In this paper, we present ProbNum: a Python library providing state-of-the-art probabilistic numerical solvers. ProbNum enables custom composition of PNMs for specific problem classes via a modular design as well as wrappers for off-the-shelf use. Tutorials, documentation, developer guides and benchmarks are available online at www.probnum.org.




Has companion code repository: https://github.com/ceciliakaiyu/mlbq








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