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GAN: Generative Adversarial Nets
Jesus
21783
NIPS
2014
GAN: Generative Adversarial Nets
Jesus
21783
NIPS
2014
cGAN: Conditional Generative Adversarial Nets
arxiv.org
3794
arXiv
2014
cGAN: Conditional Generative Adversarial Nets
arxiv.org
3794
arXiv
2014
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
๐๐
arxiv.org
2095
NIPS
2016
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
๐๐
arxiv.org
2095
NIPS
2016
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
GAN
arxiv.org
746
NIPS
2016
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
GAN
arxiv.org
746
NIPS
2016
SGAN: Semi-supervised GAN
arxiv.org
336
arXiv
2016
SGAN: Semi-supervised GAN
arxiv.org
336
arXiv
2016
catGAN: Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks
Fake vs. Categorical
Regularized Information Maximization
arxiv.org
489
ICLR
2016
catGAN: Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks
Fake vs. Categorical
Regularized Information Maximization
arxiv.org
489
ICLR
2016
ACGAN: Conditional Image Synthesis with Auxiliary Classifier GANs
๐
GAN
arxiv.org
1363
ICML
2017
ACGAN: Conditional Image Synthesis with Auxiliary Classifier GANs
๐
GAN
arxiv.org
1363
ICML
2017
LSGAN
arxiv.org
1587
ICCV
2017
LSGAN
arxiv.org
1587
ICCV
2017
W-GAN: Wasserstein GAN
arxiv.org
4966
arXiv
2017
W-GAN: Wasserstein GAN
arxiv.org
4966
arXiv
2017
WGAN-GP: Improved Training of Wasserstein GANs
gradient penalty
arxiv.org
NIPS
2017
WGAN-GP: Improved Training of Wasserstein GANs
gradient penalty
arxiv.org
NIPS
2017
DRAGAN: On Convergence and Stability of GANs
arxiv.org
163
arXiv
2017
DRAGAN: On Convergence and Stability of GANs
arxiv.org
163
arXiv
2017
DCGAN
DCGAN
Zero-Centered GP: Which Training Methods for GANs do actually Converge?
363
ICML
2018
Zero-Centered GP: Which Training Methods for GANs do actually Converge?
363
ICML
2018
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