AI engineering glossary · Generative media multimodal
What is flow matching?
Flow matching: A training framework for generative models that learns a velocity field transporting simple noise to data along smooth paths, using a simple regression loss. It often gives straighter trajectories than classic diffusion, allowing high quality with fewer sampling steps.
Flow matching: an example
Instead of predicting noise, the network predicts the direction from a noisy point toward the target image, and sampling integrates that direction.
Related terms
- Rectified flow
- Diffusion model
- Consistency model
More Generative media multimodal terms
- Forward diffusion process
- Fréchet Inception Distance
- Generative adversarial network
- Grapheme-to-phoneme
- Guidance scale
- Image captioning
- Image tokenizer
- Image-to-image translation
Where you learn it
Flow matching is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.