The Need, Benefits, and Applications of Diffusion Models

We’ve learned about what diffusion models are and how they’re used in previous lessons. Now, let’s look at their benefits, wide-ranging applications, and inherent limitations.

Benefits over other generative models

There are several benefits of diffusion models over the other generative models. Let’s discuss some of them:

• In the context of training stability, diffusion models exhibit inherent robustness, mitigating challenges associated with unstable learning dynamics GANs face.

• The progressive nature of diffusion, where samples are generated through a series of controlled diffusion steps, contributes to a stable training process.

• The diffusion process allows for fine-grained control over the generation time steps. ...