Opening the paper…
Mathematical Foundations of Generative AI, Quiz 2
In a Denoising Diffusion Probabilistic Model (DDPM), the sampling process works by running the reverse diffusion steps:
Are these reverse steps in DDPM usually stochastic (i.e., involve random noise at each step) rather than purely deterministic?
In a Denoising Diffusion Probabilistic Model (DDPM), the sampling process works by running the reverse diffusion steps: Figure from the original question paper Are these reverse steps in DDPM usually stochastic (i.e., involve random noise at each step) rather than purely deterministic? Figure from the original question paper Figure from the original question paper Figure from the original question paper A DDPM is trained with\ time steps. If the initial time step\ has a very small Figure from the original question paper Figure from the original question paper (variance), and the final time step\ has a very large\ , what is the resulting value of the Figure from the original question paper Figure from the original question paper Figure from the original question paper total added noise component\ at\ and\ ? Figure from the original question paper