Q1. Diffusion (MCQ)

Which statement best describes the forward and reverse processes in a typical diffusion model (e.g., Denoising Diffusion Probabilistic Models)?

• A single-pass network takes random noise and produces an image in one forward pass, with no iterative steps.
• During the forward process, noise is iteratively removed from real data until it becomes pure noise, and in reverse the model adds noise step by step to create new images.
• In the forward process, a small amount of noise is added to real data at each step until it becomes nearly pure noise; the reverse process is then learned to denoise step by step. <- correct
• The diffusion model relies on adversarial training where a discriminator oversees both noising and denoising.