# Contents

https://deepgenerativemodels.github.io/notes/index.html

[Contents](https://deepgenerativemodels.github.io/notes/) [Class](http://deepgenerativemodels.github.io) [Github](http://github.com/deepgenerativemodels/notes)
# Contents
These notes form a concise introductory course on deep generative models. They are based on Stanford [CS236](https://deepgenerativemodels.github.io/), taught by [Stefano Ermon](http://cs.stanford.edu/~ermon/) and [Aditya Grover](http://aditya-grover.github.io/), and have been written by [Aditya Grover](http://aditya-grover.github.io/), with the [help](https://github.com/deepgenerativemodels/notes/commits/master) of many students and course staff.  ⊕The notes are still **under construction**! Since these notes are brand new, you will find several typos. If you do, please let us know, or submit a pull request with your fixes to our [Github repository](https://github.com/deepgenerativemodels/notes).  You too may help make these notes better by submitting your improvements to us via [Github](https://github.com/deepgenerativemodels/notes).
  1. [Introduction](https://deepgenerativemodels.github.io/notes/introduction/)
  2. [Autoregressive Models](https://deepgenerativemodels.github.io/notes/autoregressive/)
  3. [Variational Autoencoders](https://deepgenerativemodels.github.io/notes/vae/)
  4. [Normalizing Flow Models](https://deepgenerativemodels.github.io/notes/flow/)
  5. [Generative Adversarial Networks](https://deepgenerativemodels.github.io/notes/gan/)

Contents - Aditya Grover
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