Fetching the paper…
Reading the bibliography…
Training Generative Adversarial Networks (GANs) is notoriously challenging.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero · 2014
Earlier work this paper cites.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
Earlier work this paper cites.
Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
Earlier work this paper cites.
Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
Fisher Yu, Yinda Zhang, Shuran Song, Ari Seff, and Jianxiong Xiao · 2015
Earlier work this paper cites.
Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Earlier work this paper cites.
Unpaired image-to-image translation using cycle-consistent adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros · 2016
Earlier work this paper cites.
Least squares generative adversarial networks
Xudong Mao, Qing Li, Haoran Xie, Raymond YK Lau, Zhen Wang, and Stephen Paul Smolley · 2016
Earlier work this paper cites.
Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros · 2016
Earlier work this paper cites.
Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2016
Earlier work this paper cites.
Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
Earlier work this paper cites.
Instance normalization: The missing ingredient for fast stylization
D Ulyanov, A Vedaldi, and VS Lempitsky · 2016
Cited alongside, same era.
Conditional image generation with pixelcnn decoders
Aaron van den Oord, Nal Kalchbrenner, Lasse Espeholt, Oriol Vinyals, Alex Graves, et al · 2016
Cited alongside, same era.
Wasserstein generative adversarial networks
Martín Arjovsky, Soumith Chintala, and Léon Bottou · 2017
Cited alongside, same era.
Modulating early visual processing by language
Harm De Vries, Florian Strub, Jérémie Mary, Hugo Larochelle, Olivier Pietquin, and Aaron C Courville · 2017
Cited alongside, same era.
A learned representation for artistic style
Vincent Dumoulin, Jonathon Shlens, and Manjunath Kudlur · 2017
Cited alongside, same era.
Convolutional sequence to sequence learning
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, and Yann Dauphin · 2017
Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
Later among the works it cites.
Shane Barratt and Rishi Sharma · 2018
Closest in time.
Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
Closest in time.
The GAN Landscape: Losses, Architectures, Regularization, and Normalization
Karol Kurach, Mario Lucic, Xiaohua Zhai, Marcin Michalski, and Sylvain Gelly · 2018
Closest in time.
Are GANs Created Equal? A Large-scale Study
Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, and Olivier Bousquet · 2018
Closest in time.
cgans with projection discriminator
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Improved training of Wasserstein GANs
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron Courville · 2017
Cited alongside, same era.
GANs trained by a two time-scale update rule converge to a Nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, Günter Klambauer, and Sepp Hochreiter · 2017
Cited alongside, same era.
Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
Cited alongside, same era.
Dynamic layer normalization for adaptive neural acoustic modeling in speech recognition
Taesup Kim, Inchul Song, and Yoshua Bengio · 2017
Cited alongside, same era.
Photo-realistic single image super-resolution using a generative adversarial network
Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, et al · 2017
Cited alongside, same era.
Conditional image synthesis with auxiliary classifier GANs
Augustus Odena, Christopher Olah, and Jonathon Shlens · 2017
Cited alongside, same era.
Takeru Miyato and Masanori Koyama · 2018
Closest in time.
Spectral normalization for generative adversarial networks
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, and Yuichi Yoshida · 2018
Closest in time.
Is generator conditioning causally related to gan performance?
Augustus Odena, Jacob Buckman, Catherine Olsson, Tom B Brown, Christopher Olah, Colin Raffel, and Ian Goodfellow · 2018
Closest in time.
Film: Visual reasoning with a general conditioning layer
Ethan Perez, Florian Strub, Harm de Vries, Vincent Dumoulin, and Aaron C. Courville · 2018
Closest in time.
Assessing generative models via precision and recall
Mehdi SM Sajjadi, Olivier Bachem, Mario Lucic, Olivier Bousquet, and Sylvain Gelly · 2018
Closest in time.
Deep generative models for distribution-preserving lossy compression
Michael Tschannen, Eirikur Agustsson, and Mario Lucic · 2018
Closest in time.
Self-attention generative adversarial networks
Han Zhang, Ian Goodfellow, Dimitris Metaxas, and Augustus Odena · 2018
Closest in time.
Understanding the effectiveness of lipschitz constraint in training of gans via gradient analysis
Zhiming Zhou, Yuxuan Song, Lantao Yu, and Yong Yu · 2018
Closest in time.