Denoising Diffusion Models Part 1: Estimating True Distribution
Code for this blog post: Notebook Github Link Colab Basic: Predicting Original Distribution Vanilla Implementation The best way to learn is by writing the maths in your notebook alongside the tutorial, or by implementing the code alongside the notebooks. What are Denoising Diffusion Models? Denoising Diffusion Models, commonly referred to as “Diffusion models”, are a class of generative models based on the Variational Auto Encoder (VAE) architecture. These models are called likelihood-based models because they assign a high likelihood to the observed data samples $p(X)$. In contrast to other generative models, such as GANs, which learn the sampling process of a complex distribution and are trained adversarially. ...