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Merge pull request #418 from JaxGaussianProcesses/fix_readme_typos
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Update README.md
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st-- authored Nov 29, 2023
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[subscribe to GPJax on CodeTriage](https://www.codetriage.com/jaxgaussianprocesses/gpjax).

As a contributor to GPJax, you are expected to abide by our [code of
conduct](docs/CODE_OF_CONDUCT.md). If you are feel that you have either experienced or
conduct](docs/CODE_OF_CONDUCT.md). If you feel that you have either experienced or
witnessed behaviour that violates this standard, then we ask that you report any such
behaviours though [this form](https://jaxgaussianprocesses.com/contact/) or reach out to
behaviours through [this form](https://jaxgaussianprocesses.com/contact/) or reach out to
one of the project's [_gardeners_](https://docs.jaxgaussianprocesses.com/GOVERNANCE/#roles).

Feel free to join our [Slack
Expand All @@ -61,7 +61,7 @@ GPJax was founded by [Thomas Pinder](https://github.com/thomaspinder). Today, th
project's gardeners are [daniel-dodd@](https://github.com/daniel-dodd),
[henrymoss@](https://github.com/henrymoss), [st--@](https://github.com/st--), and
[thomaspinder@](https://github.com/thomaspinder), listed in alphabetical order. The full
governance structure of GPJax is detailed [here](docs/GOVERNANCE.md).We appreciate all
governance structure of GPJax is detailed [here](docs/GOVERNANCE.md). We appreciate all
[the contributors to
GPJax](https://github.com/JaxGaussianProcesses/GPJax/graphs/contributors) who have
helped to shape GPJax into the package it is today.
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# Construct the prior
meanf = gpx.mean_functions.Zero()
kernel = gpx.kernels.RBF()
prior = gpx.Prior(mean_function=meanf, kernel = kernel)
prior = gpx.Prior(mean_function=meanf, kernel=kernel)

# Define a likelihood
likelihood = gpx.Gaussian(num_datapoints = n)
likelihood = gpx.Gaussian(num_datapoints=n)

# Construct the posterior
posterior = prior * likelihood
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