Cold Diffusion

Cold diffusion is a novel approach to generative modeling that replaces the traditional Gaussian noise diffusion process with deterministic image transformations, such as blurring or downsampling. Research currently focuses on applying cold diffusion to diverse tasks, including medical image segmentation, MRI reconstruction, robotic planning, and speech enhancement, often demonstrating improved performance and faster convergence compared to standard diffusion models. This technique's ability to handle arbitrary degradations and its inherent generative nature offers significant advantages for various applications, enabling improved accuracy, uncertainty quantification, and more efficient training in diverse fields.