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Update the related-package section in docs/src/index.md
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nathanaelbosch committed Sep 24, 2024
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Expand Up @@ -40,5 +40,5 @@ For a quick introduction check out the "[Solving ODEs with Probabilistic Numeric

## Related packages

- [probdiffeq](https://pnkraemer.github.io/probdiffeq/): Fast and feature-rich filtering-based probabilistic ODE solvers in JAX.
- [ProbNum](https://probnum.readthedocs.io/en/latest/): Probabilistic numerics in Python. It has not only probabilistic ODE solvers, but also probabilistic linear solvers, Bayesian quadrature, and many filtering and smoothing implementations.
- [ProbDiffEq](https://pnkraemer.github.io/probdiffeq/) is similar in scope to ProbNumDiffEq.jl and it provides fast and feature-rich probabilistic ODE solvers but is implemented in Python and built on JAX.

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[vale] reported by reviewdog 🐶
[Vale.Terms] Use 'probdiffeq' instead of 'ProbDiffEq'.

Raw Output:
{"message": "[Vale.Terms] Use 'probdiffeq' instead of 'ProbDiffEq'.", "location": {"path": "docs/src/index.md", "range": {"start": {"line": 43, "column": 4}}}, "severity": "ERROR"}
- [ProbNum](https://probnum.readthedocs.io/en/latest/) implements a wide range of probabilistic numerical methods, not only for ODEs but also for linear algebra, quadrature, and filtering/smoothing. It is implemented in Python and NumPy, and it focuses more on breadth and didactic purposes than on performance.

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