Kai Lascheit

What Is It Like to Be a Noise? An Entropy-based Gaussian Noise Regularization for Diffusion Models

Inference-time optimization of diffusion latents enables powerful control but often degrades the statistical structure of true Gaussian noise, causing artifacts and reward hacking. To address this, we propose a Gaussianity regularizer that aligns a sample's local statistics with a typical Gaussian r