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+[![Status of Build and Tests Workflow](https://github.com/aritraghsh09/GaMPEN/actions/workflows/main.yml/badge.svg)](https://github.com/aritraghsh09/GaMPEN/actions/workflows/main.yml)
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+
+<hr>
+
+![image](./intro_image.png)
+
+<hr>
+
+The Galaxy Morphology Posterior Estimation Network (GaMPEN) is a novel
+machine learning framework for estimating the Bayesian posteriors (i.e.,
+values + uncertainties) of morphological parameters for arbitrarily
+large numbers of galaxies. GaMPEN also automatically crops input galaxy
+images to an optimal size before morphological parameter estimation.
+
+GaMPEN's predicted uncertainties have been shown to be upto ~60%
+more accurate compared to traditional light-profile fitting codes. GaMPEN 
+can be adapted to work on both ground and space-based imaging;
+and to predict both parametric and non-parametric estimates of
+morphology.
+
+Once trained, it takes GaMPEN less than a milli-second to perform a
+single model evaluation on a CPU. Thus, GaMPEN's posterior prediction
+capabilities are ready for large galaxy samples expected from upcoming
+large imaging surveys, such as Rubin-LSST, Euclid, and NGRST.
+
+**For a quick read-through of why GaMPEN was developed, what challenges
+it addresses, and how it works** see this
+[link](http://gampen.ghosharitra.com/)
+
+# Documentation
+
+GaMPEN's documentation is available in this repository and also hosted 
+on [readthedocs.io](https://gampen.readthedocs.io/) . Although the documentation
+is fairly complete; if you are trying to use  GaMPEN and run into issues, 
+please get in touch with us!
+
+# Publication
+
+GaMPEN was initially introduced in this [ApJ
+paper](https://iopscience.iop.org/article/10.3847/1538-4357/ac7f9e)
+
+An updated record of GaMPEN's trained models and catalogs produced are
+maintained [here](http://gampen.ghosharitra.com/)
+
+## Attribution Info.
+Please cite the above-mentioned publication if you make use of this software
+module or some code herein.
+
+``` tex
+@article{Ghosh2022,
+author = {Aritra Ghosh and C. Megan Urry and Amrit Rau and Laurence Perreault-Levasseur and Miles Cranmer and Kevin Schawinski and Dominic Stark and Chuan Tian and Ryan Ofman and Tonima Tasnim Ananna and Connor Auge and Nico Cappelluti and David B. Sanders and Ezequiel Treister},
+doi = {10.3847/1538-4357/ac7f9e},
+issn = {0004-637X},
+issue = {2},
+journal = {The Astrophysical Journal},
+month = {8},
+pages = {138},
+title = {GaMPEN: A Machine-learning Framework for Estimating Bayesian Posteriors of Galaxy Morphological Parameters},
+volume = {935},
+year = {2022},
+}
+```
+
+# License
+
+Copyright 2022 Aritra Ghosh, Amrit Rau & contributors
+
+Made available under a [GNU GPL
+v3.0](https://github.com/aritraghsh09/GaMPEN/blob/master/LICENSE)
+license.
+
+# Contributors
+
+GaMPEN was initially developed by [Amrit Rau](https://amritrau.xyz/) and
+[Aritra Ghosh](http://www.ghosharitra.com/)
+
+The initial documentation was developed by [Aayush
+Mishra](https://github.com/aayush2505) and [Aritra
+Ghosh](http://www.ghosharitra.com/)
+
+For an updated list of all current contributors, please see
+[here](https://github.com/aritraghsh09/GaMPEN/graphs/contributors)
+
+# Getting Help/Contributing
+
+If you have a question, please send me an e-mail at this
+`aritraghsh09@xxxxx.com` GMail address.
+
+If you have spotted a bug in the code/documentation or you want to
+propose a new feature, please feel free to open an issue/a pull request
+on GitHub.