Diffusion Path

Diffusion paths, representing the trajectory of data points transforming between a simple distribution and a complex target distribution, are central to many modern generative models. Current research focuses on optimizing these paths for improved efficiency and control in tasks like image generation and out-of-distribution detection, employing techniques such as kinetic energy minimization and manipulation of intermediate latent representations within diffusion models. These advancements are improving the quality, speed, and controllability of generative models, with implications for various applications including image synthesis, editing, and anomaly detection.