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ϵθ\epsilon_\theta

This entry links every published equation using this exact notation. Its meaning may change between equations.

Used in 1 equation

Ldiffusion=Ex0, ϵ∼N(0,I), t[ ∥ϵ−ϵθ(xt,t,c)∥2 ],xt=αˉt x0+1−αˉt ϵ\mathcal{L}_{\text{diffusion}} = \mathbb{E}_{x_0,\, \epsilon \sim \mathcal{N}(0, I),\, t} \Big[\, \big\| \epsilon - \epsilon_\theta(x_t, t, c) \big\|^2 \,\Big], \qquad x_t = \sqrt{\bar{\alpha}_t}\, x_0 + \sqrt{1 - \bar{\alpha}_t}\, \epsilon

Adapters, Native Pretraining, and Unified Tokens: The Main Multimodal Architectures, Compared · Equation 12

This equation states an equality: the expressions on both sides have the same value under the article’s assumptions.

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