Pytorch Mnist Celeba Gan Dcgan
Pytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Alae | 2,850 | 3 years ago | 31 | Python | ||||||
| [CVPR2020] Adversarial Latent Autoencoders | ||||||||||
| Disentangling Vae | 668 | a year ago | 7 | other | Python | |||||
| Experiments for understanding disentanglement in VAE latent representations | ||||||||||
| Joint Vae | 384 | 5 years ago | 1 | mit | Jupyter Notebook | |||||
| Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation :star2: | ||||||||||
| Pytorch Mnist Celeba Gan Dcgan | 302 | 5 years ago | 9 | Python | ||||||
| Pytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets | ||||||||||
| Pytorch Mnist Celeba Cgan Cdcgan | 221 | 7 years ago | 6 | Python | ||||||
| Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset | ||||||||||
| Variational Ladder Autoencoder | 198 | 6 years ago | 1 | Python | ||||||
| Implementation of VLAE | ||||||||||
| Gan Tutorial | 190 | 4 years ago | Jupyter Notebook | |||||||
| Simple Implementation of many GAN models with PyTorch. | ||||||||||
| Twostagevae | 160 | 5 years ago | 7 | Python | ||||||
| Deep Learning | 128 | 6 years ago | 2 | mit | Jupyter Notebook | |||||
| Deep Learning Application Examples | ||||||||||
| Tf Exercise Gan | 109 | 6 years ago | 1 | mit | Python | |||||
| Tensorflow implementation of different GANs and their comparisions | ||||||||||
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Python
Pytorch
Generative Adversarial Network
Mnist
Adversarial Networks
Celeba
Dcgan