Flow Matching

A generative modeling framework that trains a neural network to predict a velocity field that transports samples from a simple prior distribution (e.g., Gaussian) to the data distribution along straight paths. Flow matching offers faster training and inference than diffusion models while achieving comparable or better sample quality. It is being explored as a faster alternative to diffusion policies for robot action generation.