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It is abundantly clear that time dependent data is a vital source of information in the world.
A learning algorithm for continually running fully recurrent neural networks
Ronald J Williams and David Zipser · 1989
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ImageNet: A Large-Scale Hierarchical Image Database
Jia Deng Jia Deng, Wei Dong Wei Dong, Richard Socher, Li-Jia Li-Jai Li-Jia Li, Kai Li Kai Li, and Li Fei-Fei Li Fei-Fei · 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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Scheduled sampling for sequence prediction with recurrent neural networks
Samy Bengio, Oriol Vinyals, Navdeep Jaitly, and Noam Shazeer · 2015
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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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Pixel recurrent neural networks
Aaron van den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu · 2016
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Generative adversarial text to image synthesis
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee · 2016
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C-RNN-GAN: Continuous recurrent neural networks with adversarial training
Olof Mogren · 2016
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Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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Tim Salimans, Andrej Karpathy, Xi Chen, and Diederik P Kingma · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
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Real-valued (medical) time series generation with recurrent conditional gans
Cristóbal Esteban, Stephanie L Hyland, and Gunnar Rätsch · 2017
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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.
The Great Time Series Classification Bake Off: a Review and Experimental Evaluation of Recent Algorithmic Advances
A Bagnall, J Lines, A Bostrom, J Large, and E Keogh · 2017
Cited alongside, same era.
Inception-v4, inception-resnet and the impact of residual connections on learning
Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, and Alexander A Alemi · 2017
Cited alongside, same era.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
Cited alongside, same era.
Giorgia Ramponi, Pavlos Protopapas, Marco Brambilla, and Ryan Janssen · 2018
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Robert Geirhos, Patricia Rubisch, Claudio Michaelis, Matthias Bethge, Felix A Wichmann, and Wieland Brendel · 2018
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On the convergence properties of gan training
Lars Mescheder · 2018
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Shane Barratt and Rishi Sharma · 2018
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Quantitatively evaluating GANs with divergences proposed for training
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Time series classification from scratch with deep neural networks: A strong baseline
Zhiguang Wang, Weizhong Yan, and Tim Oates · 2017
Cited alongside, same era.
Learning shape priors for single-view 3d completion and reconstruction
Jiajun Wu, Chengkai Zhang, Xiuming Zhang, Zhoutong Zhang, William T Freeman, and Joshua B Tenenbaum · 2018
Cited alongside, same era.
Large scale gan training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2018
Cited alongside, same era.
Biosignal data augmentation based on generative adversarial networks
Shota Haradal, Hideaki Hayashi, and Seiichi Uchida · 2018
Cited alongside, same era.
EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signals
Kay Gregor Hartmann, Robin Tibor Schirrmeister, and Tonio Ball · 2018
Cited alongside, same era.
Generating spiking time series with Generative Adversarial Networks: an application on banking transactions
Luca Simonetto · 2018
Cited alongside, same era.
Generative adversarial network for synthetic time series data generation in smart grids
Chi Zhang, Sanmukh R Kuppannagari, Rajgopal Kannan, and Viktor K Prasanna · 2018
Cited alongside, same era.
Daniel Jiwoong Im, He Ma, Graham Taylor, and Kristin Branson · 2018
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Are gans created equal? a large-scale study
Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, and Olivier Bousquet · 2018
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MirrorGAN: Learning Text-to-image Generation by Redescription
Tingting Qiao, Jing Zhang, Duanqing Xu, and Dacheng Tao · 2019
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Time Series Generation using a One Dimensional Wasserstein GAN
E Kaleb Smith and O Anthony Smith · 2019
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Quick and Easy Time Series Generation with Established Image-based GANs
Eoin Brophy, Zhengwei Wang, and Tomas E Ward · 2019
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Adversarial examples are a natural consequence of test error in noise
Nic Ford, Justin Gilmer, Nicolas Carlini, and Dogus Cubuk · 2019
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Benchmarking neural network robustness to common corruptions and perturbations
Dan Hendrycks and Thomas Dietterich · 2019
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Pros and cons of gan evaluation measures
Ali Borji · 2019
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