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In this paper, we show that Generative Adversarial Networks (GANs) suffer from catastrophic forgetting even when they are trained to approximate a single target distribution.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J. Cohen · 1989
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Connectionist models of recognition memory: constraints imposed by learning and forgetting functions
Roger Ratcliff · 1990
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Learning factorial codes by predictability minimization
Jürgen Schmidhuber · 1992
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Flat minima
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Catastrophic forgetting in connectionist networks
Robert M. French · 1999
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Learning multiple layers of features from tiny images
Alex Krizhevsky et al · 2009
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2015
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen, and Xi Chen · 2016
Cited alongside, same era.
Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A. Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell · 2017
Cited alongside, same era.
Wasserstein generative adversarial networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
Cited alongside, same era.
Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
Cited alongside, same era.
Gradient descent gan optimization is locally stable
Vaishnavh Nagarajan and J. Zico Kolter · 2017
Cited alongside, same era.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Which training methods for GANs do actually converge?
Lars Mescheder, Andreas Geiger, and Sebastian Nowozin · 2018
Closest in time.
Generative Adversarial Network Training is a Continual Learning Problem
Kevin J Liang, Chunyuan Li, Guoyin Wang, and Lawrence Carin · 2018
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Do GANs learn the distribution? some theory and empirics
Sanjeev Arora, Andrej Risteski, and Yi Zhang · 2018
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On the discrimination-generalization tradeoff in GANs
Pengchuan Zhang, Qiang Liu, Dengyong Zhou, Tao Xu, and Xiaodong He · 2018
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Many paths to equilibrium: GANs do not need to decrease a divergence at every step
William Fedus, Mihaela Rosca, Balaji Lakshminarayanan, Andrew M. Dai, Shakir Mohamed, and Ian Goodfellow · 2018
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Progressive growing of GANs for improved quality, stability, and variation
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Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
Cited alongside, same era.
The numerics of gans
Lars Mescheder, Sebastian Nowozin, and Andreas Geiger · 2017
Cited alongside, same era.
Continual learning in generative adversarial nets
Ari Seff, Alex Beatson, Daniel Suo, and Han Liu · 2017
Cited alongside, same era.
Generalization and equilibrium in generative adversarial nets (GANs)
Sanjeev Arora, Rong Ge, Yingyu Liang, Tengyu Ma, and Yi Zhang · 2017
Cited alongside, same era.
Learning from simulated and unsupervised images through adversarial training
Ashish Shrivastava, Tomas Pfister, Oncel Tuzel, Joshua Susskind, Wenda Wang, and Russell Webb · 2017
Cited alongside, same era.
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2018
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Progress & compress: A scalable framework for continual learning
Jonathan Schwarz, Wojciech Czarnecki, Jelena Luketina, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, and Raia Hadsell · 2018
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Wasserstein divergence for gans
Jiqing Wu, Zhiwu Huang, Janine Thoma, Dinesh Acharya, and Luc Van Gool · 2018
Closest in time.
Improving generalization and stability of generative adversarial networks
Hoang Thanh-Tung, Truyen Tran, and Svetha Venkatesh · 2019
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