--- a
+++ b/docs/references.rst
@@ -0,0 +1,26 @@
+References
+----------
+
+.. _groenbech2020:
+
+Christopher Heje Grønbech, Maximillian Fornitz Vording, Pascal N. Timshel, Casper Kaae Sønderby, Tune H. Pers, and Ole Winther (2020). "`scVAE: Variational auto-encoders for single-cell gene expression data`_". *Bioinformatics*, btaa293.
+
+.. _`scVAE: Variational auto-encoders for single-cell gene expression data`: https://doi.org/10.1093/bioinformatics/btaa293
+
+.. _kingma2014:
+
+Diederik P. Kingma and Max Welling (2014). "`Auto-encoding variational Bayes`_". *Proceedings of the 2nd International Conference on Learning Representations (ICLR)*.
+
+.. _`Auto-encoding variational Bayes`: https://arxiv.org/abs/1312.6114
+
+.. _kingma2015:
+
+Diederik P. Kingma and Jimmy Ba (2015). "`Adam: A method for stochastic optimization`_". *Proceedings of the 3rd International Conference on Learning Representations (ICLR)*.
+
+.. _`Adam: A method for stochastic optimization`: https://arxiv.org/abs/1412.6980
+
+.. _rezende2014:
+
+Danilo Jimenez Rezende, Shakir Mohamed, and Daan Wierstra (2014). "`Stochastic backpropagation and approximate inference in deep generative models`_". In: Xing, E.P. and Jebara, T. (eds.), *Proceedings of the 31st International Conference on Machine Learning*, volume 32 of *Proceedings of Machine Learning Research*, PMLR, pp. 1278--1286.
+
+.. _`Stochastic backpropagation and approximate inference in deep generative models`: https://arxiv.org/abs/1401.4082