This project implements a Variational Autoencoder (VAE) from scratch using PyTorch and applies it to the MNIST dataset. VAEs are generative models that learn to encode data into a latent space and can generate new data points from this space.
To run this project, clone the repository and run the following command in your terminal
python train.py
You may change configurations in the config.py to optimize performance on your system.
Here are a few examples of the generated outputs of digits.
