GAN

Papers of GANs

Original GAN Paper

Generative Adversarial Nets [Paper][Code]

GAN Theory

f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization [Paper]

Energy-based generative adversarial network [Paper][Code](Lecun paper)

Boundary-Seeking Generative Adversarial Networks [Paper]

Least Squares Generative Adversarial Networks [Paper][Code]

Mode Regularized Generative Adversarial Networks [Paper](Yoshua Bengio , ICLR 2017)

Improving Generative Adversarial Networks with Denoising Feature Matching [Paper][Code](Yoshua Bengio , ICLR 2017)

Sampling Generative Networks [Paper][Code]

Unrolled Generative Adversarial Networks [Paper][Code]

Lipschitz GAN

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Towards Principled Methods for Training Generative Adversarial Networks [Paper](ICLR 2017)

Wasserstein GAN [Paper][Code]

Improved Training of Wasserstein GANs [Paper][Code]

Relaxed Wasserstein, with Applications to GANs and Distributionally Robust Optimization [Paper]

Improving the Improved Training of Wasserstein GANs [Paper][Code]

Banach Wasserstein GAN [Paper][Code](NIPS 2018)

Spectral Normalization for Generative Adversarial Networks [Paper][Code](ICLR 2018)

On the regularization of Wasserstein GANs [Paper](ICLR 2018)

Generative Modeling using the Sliced Wasserstein Distance [Paper](CVPR 2018)

Max-Sliced Wasserstein Distance and its use for GANs [Paper][Code](CVPR 2019)

A Wasserstein GAN model with the total variational regularization [Paper]

Orthogonal Wasserstein GANs [Paper]

Convergence of Training Methods

GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium [Paper][code]

Which Training Methods for GANs do actually Converge [Paper][code]

Gradient descent GAN optimization is locally stable [Paper][code]

The Numerics of GANs [Paper][code](NIPS 2017)

Generalization

Generalization and Equilibrium in Generative Adversarial Nets(GANs) [Paper][Code]

Do GANs learn the distribution? Some Theory and Empirics [Paper]

Theoretical limitations of Encoder-Decoder GAN architectures [Paper]

Improving Generalization and Stability of Generative Adversarial Networks [Paper][Code]

Training Tricks

Improved Techniques for Training GANs [Paper][Code](Goodfellow's paper)

Self-Supervised Generative Adversarial Networks [Paper][code](CVPR 2019)

Joint Probability

Adversarially Learned Inference [Paper][Code]

Convergence and Stability

On Convergence and Stability of GANs [Paper] [Code] (DRAGAN)

Smoothness and Stability in GANs [Paper] (ICLR 2020)

Overview of GANs

Generative Adversarial Networks: Introduction and Outlook [Paper]

Are GANs Created Equal? A Large-Scale Study [Paper] [Code]

Generative Adversarial Network An Overview [Paper]

How Generative Adversarial Networks and Their Variants Work: An Overview [Paper]

Comparative Study on Generative Adversarial Networks [Paper]

Generative Adversarial Networks: A Survey and Taxonomy [Paper]

Recent Progress on Generative Adversarial Networks (GANs): A Survey [Paper]

A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications [Paper]

Generative Adversarial Networks (GANs): Challenges, Solutions, and Future Directions [Paper]