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Indeed, we already saw that and we can show that where The KL divergence between 2 gaussian distributions having a closed form, we will see in the next section that this upper bound defines a very tractable loss function to be minimised for the training process

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The Vial Shake: We mentioned it before, but it bears repeating

First, we notice that It implies that and, so, we can reparametrise the model by defining so that With this new parametrisation, we no longer learn a model that represent the mean of the reverse process but a model that represent the noise that has been added into x_0 to get x_t