A naukri.com initiative
Medium
4w
0
Image Credit: Medium
Build our Diffusion Model From Scratch and Understand the math
- The article describes how to build a diffusion model from scratch and understand the math behind it.
- The diffusion model is helpful in image generation and is based on a posterior distribution that represents the diffusion process.
- The article explains how to derive q(x_t-1|x_t) and q(x_t-1|x_t,x_0) distributions and makes use of the Evidence Lower Bound (ELBO) to maximize the likelihood function.
- The article also explains how to use the reparameterization trick to compute the derivative and perform backpropagation.
- Code snippets are provided to illustrate the steps involved in building the diffusion model, creating the UNet model, and calculating the loss function.
- The author acknowledges the contributions of the original paper authors Jonathan Ho, Ajay Jain, and Pieter Abbeel, and other researchers whose work this paper builds upon.
- The author also acknowledges Lil Log for her helpful blog on the mathematics involved in the diffusion model.
- The article cautions that there may be inaccuracies and encourages feedback and corrections from readers.
- Overall, the article provides a detailed explanation of the mathematics involved in building a diffusion model from scratch.
- The article also provides code snippets to illustrate the various steps involved in building the model and the UNet model.
Read Full Article
Like
For uninterrupted reading, download the app