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GANs.pdf
GANs.pdf
 
 
cgan_emnist.ipynb
cgan_emnist.ipynb
 
 
cgan_emnist.py
cgan_emnist.py
 
 
cgan_fashion.ipynb
cgan_fashion.ipynb
 
 
cgan_fashion.py
cgan_fashion.py
 
 
dcgan_celeba.ipynb
dcgan_celeba.ipynb
 
 
dcgan_celeba.py
dcgan_celeba.py
 
 
dcgan_emnist.ipynb
dcgan_emnist.ipynb
 
 
dcgan_emnist.py
dcgan_emnist.py
 
 
dcgan_fashion.ipynb
dcgan_fashion.ipynb
 
 
dcgan_fashion.py
dcgan_fashion.py
 
 
dcgan_mnist.ipynb
dcgan_mnist.ipynb
 
 
dcgan_mnist.py
dcgan_mnist.py
 
 
gan_celeba.ipynb
gan_celeba.ipynb
 
 
gan_celeba.py
gan_celeba.py
 
 
gan_cifar.ipynb
gan_cifar.ipynb
 
 
gan_cifar.py
gan_cifar.py
 
 
gan_emnist.ipynb
gan_emnist.ipynb
 
 
gan_emnist.py
gan_emnist.py
 
 
gan_mnist.ipynb
gan_mnist.ipynb
 
 
gan_mnist.py
gan_mnist.py
 
 

About

Implemented and experimented with GAN, Conditional GAN and Deep-Convolutional GAN on various datasets for comparison, learning and demonstration purposes

Topics

pytorch generative-adversarial-network gan dcgan celeba cifar10 cgan fashion-mnist scratch-implementation mnist-digits
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