Foundations of Diffusion Models and How DDPM Works
Diffusion models have emerged as a groundbreaking approach in the landscape of deep generative models, offering a robust alternative to traditional methods like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). These models are based on a stochastic process that gradually transforms data into a distribution of pure noise and