https://github.com/dyth/generative_models
https://github.com/dyth/generative_models
autoencoders cifar-10 gan mnist
Last synced: 12 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/dyth/generative_models
- Owner: dyth
- License: mit
- Created: 2019-04-02T03:05:10.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2020-06-15T23:32:21.000Z (about 6 years ago)
- Last Synced: 2025-03-02T02:33:59.422Z (over 1 year ago)
- Topics: autoencoders, cifar-10, gan, mnist
- Language: Python
- Size: 65.4 KB
- Stars: 1
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Generative Models
Implementation of famous models for self-study
## Autoencoders
* feedforward (MNIST)
* convolutional (MNIST)
* residual (MNIST)
* variational (MNIST, CIFAR)
* beta-variational (MNIST)
* convolutional with perceptual loss (MNIST)
## GANs
* GAN (MNIST)
* DCGAN (MNIST)
## References
[https://github.com/eriklindernoren/PyTorch-GAN] and
[https://github.com/lyeoni/pytorch-mnist-GAN] were very helpful in understanding
how the mathematics of GANs translated to code; as well as providing good
initial hyperparameters and architectures