Variational Autoencoder using MNIST dataset
Colab Demo
Examples
Description
TODO
Links
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| Exploring Latent Space |
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| Some examples from test set |
Another one Variational Autoencoder trained on MNIST
Weights:
- Create VAE training pipeline and train
- Architecture
- BCE loss instead of MSE
- Convolutional Pooling instead of MaxPool
- Train Autoencoder
- Train Fully-Coonvolutional AE
- Train Variational Autoencoder
- Train Fully-Coonvolutional VAE
- Compare different architectures (Need some metric)
- Minimum working example in Colab
- Train VAE on different dataset (ex. CelebA)
Github: Pytorch Examples
Arxiv: Auto-Encoding Variational Bayes