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10. Reconsturcting Inputs using Autoencoders

Name		Name	Last commit message	Last commit date
parent directory ..
.ipynb_checkpoints		.ipynb_checkpoints
10.03 Reconstructing MNIST images using Autoencoder.ipynb		10.03 Reconstructing MNIST images using Autoencoder.ipynb
10.05 Building Convolutional Autoencoder.ipynb		10.05 Building Convolutional Autoencoder.ipynb
10.07 Denoising images using Denoising Autoencoder.ipynb		10.07 Denoising images using Denoising Autoencoder.ipynb
10.09 Building the Sparse Autoencoder.ipynb		10.09 Building the Sparse Autoencoder.ipynb
10.11 Implementing Contractive Autoencoders.ipynb		10.11 Implementing Contractive Autoencoders.ipynb
10.13 Generating images using VAE.ipynb		10.13 Generating images using VAE.ipynb
README.md		README.md

10.1. What is Autoencoder?
10.2. Understanding the architecture of autoencoders
10.3. Reconstructing MNIST images using autoencoders
10.4. Autoencoders with convolution
10.5. Building convolution autoencoder
10.6. Exploring denoising autoencoder
10.7. Denoising images using DAE
10.8. Understanding sparse autoencoders
10.9. Building sparse autoencoders
10.10. Learning to use contractive autoencoders
10.11. Implementing contractive autoencoders
10.12. Dissecting variational autoencoders
- 10.12.1. Variational Inferrence
- 10.12.2. Loss Function
- 10.12.3. Reparamterisation Trick
10.13. Generating images using VAE