Build a Stable Diffusion VAE From Scratch Using PyTorch

Follow along with a 43-minute tutorial demonstrating how to implement and train a Variational Autoencoder (VAE) from scratch using PyTorch. Dive deep into the architecture of VAEs, a specialized type of neural network that employs unsupervised learning techniques commonly used in image generation models, particularly in latent diffusion-based and GANs-based systems. Access the complete training code through the provided Colab notebook and explore a detailed article explaining VAE concepts and implementation details. Master the fundamentals of building essential components used in popular image generation models like Stable Diffusion while gaining hands-on experience with PyTorch development.