Fix up citable link

CITATION.md

@@ -0,0 +1,27 @@
+# Citing
+
+This software:
+```
+@software{pysr,
+  author       = {Miles Cranmer},
+  title        = {PySR: Fast & Parallelized Symbolic Regression in Python/Julia},
+  month        = sep,
+  year         = 2020,
+  publisher    = {Zenodo},
+  doi          = {10.5281/zenodo.4052869},
+  url          = {https://doi.org/10.5281/zenodo.4052869}
+}
+```
+
+Metric used for scoring equations:
+```
+@article{cranmer2020discovering,
+      title={Discovering Symbolic Models from Deep Learning with Inductive Biases}, 
+      author={Miles Cranmer and Alvaro Sanchez-Gonzalez and Peter Battaglia and Rui Xu and Kyle Cranmer and David Spergel and Shirley Ho},
+      journal={NeurIPS 2020},
+      year={2020},
+      eprint={2006.11287},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG}
+}
+```

README.md

@@ -1,12 +1,16 @@
 # PySR.jl
 
-[![DOI](https://zenodo.org/badge/295391759.svg)](https://zenodo.org/badge/latestdoi/295391759)
+[![Documentation Status](https://readthedocs.org/projects/pysr/badge/?version=latest)](https://pysr.readthedocs.io/en/latest/?badge=latest)
 [![PyPI version](https://badge.fury.io/py/pysr.svg)](https://badge.fury.io/py/pysr)
 [![Build Status](https://travis-ci.com/MilesCranmer/PySR.svg?branch=master)](https://travis-ci.com/MilesCranmer/PySR)
 
 **Symbolic regression built on Julia, and interfaced by Python.
 Uses regularized evolution, simulated annealing, and gradient-free optimization.**
 
+[Cite this software](https://github.com/MilesCranmer/PySR/blob/master/CITATION.md)
+
+[Documentation](https://pysr.readthedocs.io/en/latest)
+
 Symbolic regression is a very interpretable machine learning algorithm
 for low-dimensional problems: these tools search equation space
 to find algebraic relations that approximate a dataset.