Submitted by Individual-Cause-616 t3_10m4l0b in MachineLearning
jimmymvp t1_j67uru2 wrote
Diffusion models are effectively score-based, there's a connection with the reversal of the forward process being Gaussian and the noise estimate, effectively you're using scores of Gaussians in the reverse process. The time variable is irrelevant in sense of scale, the discrete time and continuous time essentially do roughly the same, the difference is that one is tied to a specific discretization of the SDE and the other can be solved to arbitrary precision, it's also a difference if you take steps wrt to variance or wrt time. Essentially the continuous formulation should be the limit of the discrete one. So effectively you can take a discrete sampling method and make it a continuous SDE/ODE
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