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Merge pull request #1520 from pints-team/first-examples
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Updated first examples to show model-free case.
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MichaelClerx authored Dec 18, 2024
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# What is Pints?

PINTS (Probabilistic Inference on Noisy Time-Series) is a framework for optimisation and Bayesian inference on ODE models of noisy time-series, such as arise in electrochemistry and cardiac electrophysiology.
PINTS (Probabilistic Inference on Noisy Time-Series) is a framework for optimisation and Bayesian inference.
Although it can be used as a general-purpose inference tool, it was developed specifically for models of noisy time-series, such as arise in electrochemistry and cardiac electrophysiology.

PINTS is described in [this publication in JORS](http://doi.org/10.5334/jors.252), and can be cited using the information given in our [CITATION file](https://github.com/pints-team/pints/blob/main/CITATION).
More information about PINTS papers can be found in the [papers directory](https://github.com/pints-team/pints/tree/main/papers).
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