Diffusion Trajectory

Diffusion trajectory research focuses on optimizing the process of generating data samples using diffusion models, aiming to improve speed and quality while maintaining accuracy. Current efforts concentrate on refining sampling algorithms, such as developing methods that enforce consistency across different stages of the diffusion process and leveraging pre-trained models or incorporating techniques like optimal transport to accelerate convergence. These advancements are significantly impacting various fields, including image reconstruction, medical imaging, and anomaly detection, by enabling faster and more efficient generation of high-quality data from complex distributions.