Generative Vision Atlas

Objective option

Drifting field

Learn the generator mapping itself and evolve its pushforward distribution during training until it matches the data, rather than learning a score or velocity to integrate at sampling time.

Introduced by

Used by (1)

Drifting Models

Alternatives on this axis

Diffusion-loss autoregression, Diffusion (epsilon/v/x0-prediction), Flow matching / rectified flow, Stochastic interpolant framework, Average (mean) velocity, Next-scale autoregression, Normalizing flow, Transition matching

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