Submitted by SleekEagle t3_ye0iw7 in MachineLearning
Serverside t1_itxsq3p wrote
Reply to comment by SleekEagle in [D] Poisson Flow Generative Models - new physics inspired generative model by SleekEagle
Yeah you essentially answered what I was asking. I was basically asking if the output of a trained PFGM matched (or closely estimated) the empirical distribution of the training data. Since the end product of the “diffusion” was said to be a uniform distribution and the equations were ODEs not SDEs, I was having trouble wrapping my head around how the PFGM could be empirically matching the distribution. Thanks for answering all the questions!
SleekEagle OP t1_itzjvvo wrote
Got it! Yeah the ultimate crux of it is the proof that any continuous compact distribution has a field that approaches uniform flux density at infinity
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