DDN: Discrete Distribution Networks

DDN is a novel generative model that approximates data distributions using hierarchical discrete distributions. It generates multiple discrete samples per layer and selects the one closest to the ground truth, feeding it back as conditioning for the next layer to refine details. The approach supports zero-shot conditional generation across domains, with experiments on CIFAR-10 and FFHQ using single-shot and recurrence-iteration paradigms.