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README.md

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 <img src="https://github.com/thoglu/jammy_flows/workflows/build/badge.svg"> <img src="https://github.com/thoglu/jammy_flows/workflows/tests/badge.svg">
 
-This package implements (conditional) PDFs with **J**oint **A**utoregressive **M**anifold (**MY**) normalizing-flows. It grew out of work for the paper [Unifying supervised learning and VAEs - automating statistical inference in (astro-)particle physics with amortized conditional normalizing flows [arXiv:2008.05825]](https://arxiv.org/abs/2008.05825) and includes the paper's described methodology for coverage calculation of PDFs on tensor products of manifolds. For Euclidean manifolds, it includes an updated implementation of the [offical implementation](https://github.com/chenlin9/Gaussianization_Flows) of [Gaussianization flows [arXiv:2003.01941]](https://arxiv.org/abs/2003.01941), where now the inverse is differentiable (adding Newton iterations to the bisection) and made more stable using better approximations of the inverse Gaussian CDF. Several other state-of-the art flows are implemented sometimes using slight modifications or extensions.
+This package implements (conditional) PDFs with **J**oint **A**utoregressive **M**anifold (**MY**) normalizing-flows. It grew out of work for the paper [Unifying supervised learning and VAEs - coverage, systematics and goodness-of-fit in normalizing-flow based neural network models for astro-particle reconstructions [arXiv:2008.05825]](https://arxiv.org/abs/2008.05825) and includes the paper's described methodology for coverage calculation of PDFs on tensor products of manifolds. For Euclidean manifolds, it includes an updated implementation of the [offical implementation](https://github.com/chenlin9/Gaussianization_Flows) of [Gaussianization flows [arXiv:2003.01941]](https://arxiv.org/abs/2003.01941), where now the inverse is differentiable (adding Newton iterations to the bisection) and made more stable using better approximations of the inverse Gaussian CDF. Several other state-of-the art flows are implemented sometimes using slight modifications or extensions.
 
 The package has a simple syntax that lets the user define a PDF and get going with a single line of code that **should just work**. To define a 10-d PDF, with 4 Euclidean dimensions, followed by a 2-sphere, followed again by 4 Euclidean dimensions, one could for example write
 ```