Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: ProbNum: Probabilistic Numerics in Python   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.

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The categories of this paper are: hep-ex
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The categories of this paper are: dg-ga
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The categories of this paper are: patt-sol
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The categories of this paper are: comp-gas
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The categories of this paper are: adap-org
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The categories of this paper are: hep-ph
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The categories of this paper are: q-alg
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The categories of this paper are: bayes-an
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The categories of this paper are: ao-sci
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The categories of this paper are: mtrl-th
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The categories of this paper are: funct-an
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The categories of this paper are: plasm-ph
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The categories of this paper are: eess
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The categories of this paper are: hep-lat
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The categories of this paper are: nucl-th
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The categories of this paper are: quant-ph