DDPM on CIFAR-10

Key Insight

Moving a DDPM (Denoising Diffusion Probabilistic Model) from grayscale MNIST digits to 32×32 color CIFAR-10 photos is the jump from "it works on a toy" to "I actually understand this," because natural images carry texture, color, and structure that a too-small U-Net simply cannot capture. The standard bar is a FID (Fréchet Inception Distance) below 20 — FID scores how close your generated images are to real ones by comparing them in the feature space of a pretrained image classifier, where lower means more realistic — and clearing it forces you to get the noise schedule, model capacity, and training length all right at once. The payoff is a model whose samples are recognizable objects rather than colorful blobs, plus the confidence that the core recipe scales beyond toy data.