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Diffusion models in practice So far we have defined a forward process q acting as our (discretised) diffusion process that progressively destroy information as well as a backward process p_ modelling the reverse process to be learned and supposed to progressively restore the information We have then seen that training our reverse process consists in finding _ and _ that minimise the upper bound At this point it is worth noting that the different terms in the upper bound expression are independent from each others if we omit that parameters of the reverse model to be learned are shared between steps

[DOI] [PubMed] [Google Scholar] 244.Kokot A

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TGF-beta increases glioma-initiating cell self-renewal through the induction of LIF in human glioblastoma