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Incorporated reviewer comments on first-example notebooks.
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README.md

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# What is Pints?
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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.
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PINTS (Probabilistic Inference on Noisy Time-Series) is a framework for optimisation and Bayesian inference.
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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.
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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).
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More information about PINTS papers can be found in the [papers directory](https://github.com/pints-team/pints/tree/main/papers).

examples/optimisation/first-example.ipynb

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