Please list adversarial papers to look at here.
| Owner |
Paper |
Authors |
| James |
Image-to-Image Translation with Conditional Adversarial Networks |
Isola et al |
| Amos |
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks (aka Eyescream) |
Emily Denton, Soumith Chintala, Arthur Szlam, Rob Fergus |
| James (& Elliot) |
Generative Adversarial Nets |
Goodfellow et al |
| James |
A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models |
Finn et al |
| Gavin (? / Matt) |
Energy-based Generative Adversarial Networks |
Zhao, Mathieu and LeCun |
| Matt |
Generative Adversarial Networks as Variational Training of Energy Based Models |
Zhai, Cheng, Feris and Zhang |
| Matt |
Calibrating Energy-based Generative Adversarial Networks |
Dai, Almahairi, Bachman, Hovy and Courville |
| Matt |
Learning to Draw Samples: With Application to Amortized MLE for Generative Adversarial Learning |
Wang and Liu |
| Antreas |
Unrolled Generative Adversarial Networks |
Luke Metz, Ben Poole, David Pfau, and Jascha Sohl-Dickstein |
| Antreas |
Connecting Generative Adversarial Networks and Actor-Critic Methods |
David Pfau, Oriol Vinyals |
| Antreas |
Generative Multi-Adversarial Networks |
Ishan Durugkar, Ian Gemp, Sridhar Mahadevan |
| Gavin |
Improved Techniques for Training GANs |
Salimans et al |
| Gavin |
Disentangling factors of variation in deep representations using adversarial training |
Mathieu et al |
| Gavin |
Conditional Image Synthesis with Auxiliary Classifier GANs |
Odena, Olah and Shlens |
| Gavin |
Synthesizing the preferred inputs for neurons in neural networks via deep generator networks |
Nguyen et al |
| Elliot |
Unsupervised Cross-Domain Image Generation |
Taigman, Polyak and Wolf |
| Elliot |
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks |
Alec Radford, Luke Metz, Soumith Chintala |
| Amos |
Infogan: Interpretable representation learning by information maximizing generative adversarial nets |
Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, Pieter Abbeel |
| Amos |
Domain-Adversarial Neural Networks |
Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand |
| Amos |
How (not) to Train your Generative Model: Scheduled Sampling, Likelihood, Adversary? |
Ferenc Huszár |
| Amos |
Learning What and Where to Draw |
Scott Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele, Honglak Lee |
| Amos |
Why are deep nets reversible: A simple theory, with implications for training |
Sanjeev Arora, Yingyu Liang, Tengyu Ma |
| Amos |
Learning to Pivot with Adversarial Networks |
Gilles Louppe, Michael Kagan, Kyle Cranmer |
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AmosStorkey - 22 Nov 2016
Topic revision: r11 - 25 Nov 2016 - 13:20:27 - Main.s0816700
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