Instructor
 |
|---|
| Kevin McGuinness (KM) |
Videos
- Sirajology, “Generative Adversarial Nets”. Fresh Machine Learning, July 2016.
Tutorials
-
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.
-
O’Shea Research, MNIST Generative Adversarial Model in Keras. July 2016.
-
Brandon Amos, “Image Completion with Deep Learning in TensorFlow”. 2016.
Related Work & Resources
-
Szegedy, Christian, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus. “Intriguing properties of neural networks.” arXiv preprint arXiv:1312.6199 (2013). [UPC slides]
-
Practical Black-Box Attacks against Deep Learning Systems using Adversarial Examples
-
Im, Daniel Jiwoong, Chris Dongjoo Kim, Hui Jiang, and Roland Memisevic. “Generating images with recurrent adversarial networks.” arXiv preprint arXiv:1602.05110 (2016). [software]
-
Radford, Alec, Luke Metz, and Soumith Chintala. “Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks.” arXiv preprint arXiv:1511.06434 (2015). [Theano] [TensorFlow] [reddit]
-
Dumoulin, Vincent, Ishmael Belghazi, Ben Poole, Alex Lamb, Martin Arjovsky, Olivier Mastropietro, and Aaron Courville. “Adversarially Learned Inference.” arXiv preprint arXiv:1606.00704 (2016).
-
Donahue, Jeff, Philipp Krähenbühl, and Trevor Darrell. “Adversarial Feature Learning.” arXiv preprint arXiv:1605.09782 (2016).
-
Goodfellow, Ian, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. “Generative adversarial nets.” In Advances in Neural Information Processing Systems, pp. 2672-2680. 2014.
-
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)
-
Denton, Emily L., Soumith Chintala, and Rob Fergus. “Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks.” In Advances in neural information processing systems, pp. 1486-1494. 2015.
-
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.
-
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).
-
Russ Salakhutdinov, Learning Deep Generative Models. Carnegie Mellon University, 2016.