Kernel Density Steering for Image Restoration
Training-free inference-time guidance for diffusion models
Proposed Kernel Density Steering (KDS), a novel technique to guide sampling-based restoration methods toward high-quality solutions at inference time. Used KDS to effectively guide posterior sampling, significantly improving the performance of diffusion models on various image restoration tasks. Work done during Google internship. Accepted to NeurIPS 2025.