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[1] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[2] Sebastian Nowozin,et al. Which Training Methods for GANs do actually Converge? , 2018, ICML.
[3] Léon Bottou,et al. Wasserstein GAN , 2017, ArXiv.
[4] Nicolas Courty,et al. Optimal Transport for Domain Adaptation , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[5] Gabriel Peyré,et al. Fast Optimal Transport Averaging of Neuroimaging Data , 2015, IPMI.
[6] Philip Bachman,et al. Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data , 2018, ICML.
[7] Sebastian Nowozin,et al. f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization , 2016, NIPS.
[8] Shoichiro Yamaguchi,et al. Distributional Concavity Regularization for GANs , 2018, ICLR.
[9] Kelvin Shuangjian Zhang,et al. Implicit Manifold Learning on Generative Adversarial Networks , 2017, 1710.11260.
[10] Roberto Cominetti,et al. Asymptotic analysis of the exponential penalty trajectory in linear programming , 1994, Math. Program..
[11] David Lopez-Paz,et al. Geometrical Insights for Implicit Generative Modeling , 2017, Braverman Readings in Machine Learning.
[12] Marco Cuturi,et al. Sinkhorn Distances: Lightspeed Computation of Optimal Transport , 2013, NIPS.
[13] Vivien Seguy,et al. Smooth and Sparse Optimal Transport , 2017, AISTATS.
[14] Gabriel Peyré,et al. Learning Generative Models with Sinkhorn Divergences , 2017, AISTATS.
[15] Yuichi Yoshida,et al. Spectral Normalization for Generative Adversarial Networks , 2018, ICLR.
[16] Yong Yu,et al. Guiding the One-to-one Mapping in CycleGAN via Optimal Transport , 2018, AAAI.
[17] Han Zhang,et al. Improving GANs Using Optimal Transport , 2018, ICLR.
[18] L. Ambrosio,et al. Gradient Flows: In Metric Spaces and in the Space of Probability Measures , 2005 .
[19] Jason D. Lee,et al. On the Convergence and Robustness of Training GANs with Regularized Optimal Transport , 2018, NeurIPS.
[20] Jason D. Lee,et al. Solving Approximate Wasserstein GANs to Stationarity , 2018, ArXiv.
[21] Aaron C. Courville,et al. Improved Training of Wasserstein GANs , 2017, NIPS.
[22] L. Ambrosio,et al. A User’s Guide to Optimal Transport , 2013 .
[23] Shing-Tung Yau,et al. A Geometric View of Optimal Transportation and Generative Model , 2017, Comput. Aided Geom. Des..
[24] C. Villani. Optimal Transport: Old and New , 2008 .
[25] Gabriel Peyré,et al. Computational Optimal Transport , 2018, Found. Trends Mach. Learn..
[26] Gabriel Peyré,et al. Stochastic Optimization for Large-scale Optimal Transport , 2016, NIPS.
[27] Arnaud Doucet,et al. Fast Computation of Wasserstein Barycenters , 2013, ICML.
[28] Tong Zhang,et al. Composite Functional Gradient Learning of Generative Adversarial Models , 2018, ICML.
[29] Alexei A. Efros,et al. Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[30] Jacob Abernethy,et al. On Convergence and Stability of GANs , 2018 .
[31] F. Santambrogio. {Euclidean, metric, and Wasserstein} gradient flows: an overview , 2016, 1609.03890.
[32] Hongyuan Zha,et al. A Fast Proximal Point Method for Wasserstein Distance , 2018, ArXiv.
[33] J. Zico Kolter,et al. Gradient descent GAN optimization is locally stable , 2017, NIPS.
[34] Denis Lukovnikov,et al. On the regularization of Wasserstein GANs , 2017, ICLR.
[35] Ashish Khetan,et al. PacGAN: The Power of Two Samples in Generative Adversarial Networks , 2017, IEEE Journal on Selected Areas in Information Theory.
[36] Y. Brenier. Polar Factorization and Monotone Rearrangement of Vector-Valued Functions , 1991 .
[37] Hongyuan Zha,et al. A Fast Proximal Point Method for Computing Exact Wasserstein Distance , 2018, UAI.
[38] Nicolas Courty,et al. Large Scale Optimal Transport and Mapping Estimation , 2017, ICLR.