This section of our repository holds reviews of research papers that we think everyone in the field should read and understand. It currently includes:

1. [DRAW: A Recurrent Neural Network For Image Generation](https://github.com/tensorflow/magenta/blob/master/magenta/reviews/draw.md) by Gregor et al. (Review by Tim Cooijmans)
2. [Generating Sequences with Recurrent Neural Networks](https://github.com/tensorflow/magenta/blob/master/magenta/reviews/summary_generation_sequences.md) by Graves. (Review by David Ha)
3. [A Neural Algorithm of Artistic Style](https://github.com/tensorflow/magenta/blob/master/magenta/reviews/styletransfer.md) by Gatys et al. (Review by Cinjon Resnick)
4. [Pixel Recurrent Neural Networks](https://github.com/tensorflow/magenta/blob/master/magenta/reviews/pixelrnn.md) by Van den Oord et al. (Review by Kyle Kastner)
5. [Generative Adversarial Networks](https://github.com/tensorflow/magenta/blob/master/magenta/reviews/GAN.md) by Goodfellow et al. (Review by Max Strakhov)
6. [Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription](https://github.com/tensorflow/magenta/blob/master/magenta/reviews/rnnrbm.md) by Boulanger-Lewandowski et al. (Review by Dan Shiebler)

There are certainly many other papers and resources that belong here. We want this to be a community endeavor and encourage high-quality summaries, both in terms of reviews and selection. So if you have a favorite, please file an issue saying which paper you want to write about. After we approve the topic, submit a pull request and we’ll be delighted to showcase your work.