Flow Matching
A generative modeling framework that trains continuous normalizing flows by regressing vector fields, offering an efficient alternative to standard diffusion.
Think of It Like This
Like teaching a boat how to navigate a complex river by mapping out the exact speed and direction of the water currents at every single point along the way.
Flow matching provides a mathematically rigorous formulation for training continuous-time generative models. Unlike traditional diffusion models that rely on simulating complex stochastic differential equations, flow matching constructs simple, targeted vector fields. This results in faster convergence during training and highly efficient sampling during generation.