What Is It Like to Be a Noise? An Entropy-based Gaussian Noise Regularization for Diffusion ModelsBuobe IA context · why it matters Aligning local statistics with Gaussian realizations — This ensures more natural-looking results without losing control over diffusion latents. Addressing degradation of true Gaussian noise — Prevents artifacts and reward hacking, improving the quality of generated samples. Fique de olho Improved regularization could lead to broader applications in generative models. Published bystudios.disneyresearch.comon •1 min readWhat Is It Like to Be a Noise? An Entropy-based Gaussian Noise Regularization for Diffusion ModelsVisual ComputingVideo ProcessingLearn moreShareLegalReport
