diffusion models
A new measure-theoretic framework unifies diffusion, score-based, and flow matching generative models — the mathematical backbone of modern AI video and image synthesis systems.
flow matching
A technical deep dive into ODE solvers powering flow matching generative models, comparing Euler, Heun, Runge-Kutta, and adaptive Dormand-Prince methods that determine sample quality in modern video and image synthesis.
flow matching
New research proposes eliminating ODE solvers from flow matching models, enabling high-quality one-step image generation with major efficiency gains for real-time synthetic media applications.