Instructor

Kevin McGuinness (KM)

• Slides

Video lecture

(to be added)

Related work

• Radford, Alec, Luke Metz, and Soumith Chintala. “Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks.” International Conference on Learning Representations (2016). [software] [software Theano] [software TensorFlow] [demo] [related blogpost]

• Eric Jian, [“Understanding and Implementing Deepmind’s DRAW Model”] (http://evjang.com/articles/draw)

• Eslami, S. M., Nicolas Heess, Theophane Weber, Yuval Tassa, Koray Kavukcuoglu, and Geoffrey E. Hinton. “Attend, Infer, Repeat: Fast Scene Understanding with Generative Models.” 2016. [video]

• Larsen, Anders Boesen Lindbo, Søren Kaae Sønderby, and Ole Winther. “Autoencoding beyond pixels using a learned similarity metric.” arXiv preprint arXiv:1512.09300 (2015).

• Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell and Alexei A. Efros. Context Encoders: Feature Learning by Inpainting. In CVPR 2016.

• ANDREJ KARPATHY, PIETER ABBEEL, GREG BROCKMAN, PETER CHEN, VICKI CHEUNG, ROCKY DUAN, IAN GOODFELLOW, DURK KINGMA, JONATHAN HO, REIN HOUTHOOFT, TIM SALIMANS, JOHN SCHULMAN, ILYA SUTSKEVER, AND WOJCIECH ZAREMBA, “Generative models”. OpenAI 2016.

• Reed, Scott, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee. “Generative adversarial text to image synthesis.” arXiv preprint arXiv:1605.05396 (2016).

• Aaron van den Oord, Nal Kalchbrenner, Oriol Vinyals, Lasse Espeholt, Alex Graves, Koray Kavukcuoglu, “Conditional Image Generation with PixelCNN Decoders”, arXiv preprint arXiv:1606.05328 (2016).