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The wide applications of Generative adversarial networks benefit from the successful training methods, guaranteeing that an object function converges to the local minima.
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Deep learning face attributes in the wild
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f-gan: Training generative neural samplers using variational divergence minimization
S. Nowozin, B. Cseke, and R. Tomioka · 2016
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Unsupervised representation learning with deep convolutional generative adversarial networks, 2016
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Generating videos with scene dynamics
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Unified convergence analysis of stochastic momentum methods for convex and non-convex optimization, 2016
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Scan: Structure correcting adversarial network for organ segmentation in chest x-rays, 2017
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Voice conversion from unaligned corpora using variational autoencoding wasserstein generative adversarial networks, 2017
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Learning to discover cross-domain relations with generative adversarial networks, 2017
T. Kim, M. Cha, H. Kim, J. K. Lee, and J. Kim · 2017
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Deblurgan: Blind motion deblurring using conditional adversarial networks
O. Kupyn, V. Budzan, M. Mykhailych, D. Mishkin, and J. Matas · 2017
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Photo-realistic single image super-resolution using a generative adversarial network, 2017
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First-order methods almost always avoid saddle points, 2017
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Mocogan: Decomposing motion and content for video generation, 2017
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Feudal networks for hierarchical reinforcement learning, 2017
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The pose knows: Video forecasting by generating pose futures, 2017
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Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling, 2017
J. Wu, C. Zhang, T. Xue, W. T. Freeman, and J. B. Tenenbaum · 2017
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Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms, 2017
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Interaction matters: A note on non-asymptotic local convergence of generative adversarial networks, 2019
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Deep generative adversarial neural networks for compressive sensing mri
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Open questions about generative adversarial networks
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Trajectory of Alternating Direction Method of Multipliers and Adaptive Acceleration
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Taming gans with lookahead-minmax, 2020
T. Chavdarova, M. Pagliardini, S. U. Stich, F. Fleuret, and M. Jaggi · 2020
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D. Yang, T. Xiong, D. Xu, Q. Huang, D. Liu, S. K. Zhou, Z. Xu, J. Park, M. Chen, T. D. Tran, S. P. Chin, D. Metaxas, and D. Comaniciu · 2017
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Seqgan: Sequence generative adversarial nets with policy gradient, 2017
L. Yu, W. Zhang, J. Wang, and Y. Yu · 2017
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The mechanics of n-player differentiable games
D. Balduzzi, S. Racaniere, J. Martens, J. Foerster, K. Tuyls, and T. Graepel · 2018
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Polyphonic music generation with sequence generative adversarial networks, 2018
S. gil Lee, U. Hwang, S. Min, and S. Yoon · 2018
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Objective-reinforced generative adversarial networks (organ) for sequence generation models, 2018
G. L. Guimaraes, B. Sanchez-Lengeling, C. Outeiral, P. L. C. Farias, and A. Aspuru-Guzik · 2018
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Adversarial ranking for language generation, 2018
K. Lin, D. Li, X. He, Z. Zhang, and M.-T. Sun · 2018
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The numerics of gans, 2018
L. Mescheder, S. Nowozin, and A. Geiger · 2018
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D. Croce, G. Castellucci, and R. Basili · 2020
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A variational inequality perspective on generative adversarial networks, 2020
G. Gidel, H. Berard, G. Vignoud, P. Vincent, and S. Lacoste-Julien · 2020
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Training gans with predictive projection centripetal acceleration, 2020
L. Keke, Z. Ke, L. Qiang, and Y. Xinmin · 2020
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Deep reinforcement learning for multiobjective optimization
K. Li, T. Zhang, and R. Wang · 2020
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Revisiting stochastic extragradient
K. Mishchenko, D. Kovalev, E. Shulgin, P. Richtarik, and Y. Malitsky · 2020
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A unified analysis of extra-gradient and optimistic gradient methods for saddle point problems: Proximal point approach
A. Mokhtari, A. Ozdaglar, and S. Pattathil · 2020
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Training gans with centripetal acceleration
W. Peng, Y.-H. Dai, H. Zhang, and L. Cheng · 2020
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Training generative adversarial networks by solving ordinary differential equations, 2020
C. Qin, Y. Wu, J. T. Springenberg, A. Brock, J. Donahue, T. P. Lillicrap, and P. Kohli · 2020
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Lookahead converges to stationary points of smooth non-convex functions
J. Wang, V. Tantia, N. Ballas, and M. Rabbat · 2020
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A mathematical introduction to generative adversarial nets (gan), 2020
Y. Wang · 2020
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Dual adversarial network: Toward real-world noise removal and noise generation, 2020
Z. Yue, Q. Zhao, L. Zhang, and D. Meng · 2020
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Convergence of gradient methods on bilinear zero-sum games, 2020
G. Zhang and Y. Yu · 2020
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Unpaired image-to-image translation using cycle-consistent adversarial networks, 2020
J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros · 2020
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