Can anyone help me with understanding how the $\widetilde{\beta}$$\tilde{\beta}$ and ${\tilde\mu_t{(x_t, x_0)}}$ are derived?
It seems to me that exponential term is a 2nd order polynomial term and it doesn't really look like a gaussian in the form of $\frac{(x - \mu)^2}{2\sigma^2}$.
Source:https://lilianweng.github.io/posts/2021-07-11-diffusion-models/#reverse-diffusion-process
Can anyone help me with understanding how the $\widetilde{\beta}$ and ${\tilde\mu_t{(x_t, x_0)}}$ are derived?
It seems to me that exponential term is a 2nd order polynomial term and it doesn't really look like a gaussian in the form of $\frac{(x - \mu)^2}{2\sigma^2}$.
Source:https://lilianweng.github.io/posts/2021-07-11-diffusion-models/#reverse-diffusion-process
Can anyone help me with understanding how the $\tilde{\beta}$ and ${\tilde\mu_t{(x_t, x_0)}}$ are derived?
It seems to me that exponential term is a 2nd order polynomial term and it doesn't really look like a gaussian in the form of $\frac{(x - \mu)^2}{2\sigma^2}$.
Source:https://lilianweng.github.io/posts/2021-07-11-diffusion-models/#reverse-diffusion-process
Can anyone help me with understanding how the $\widetilde{\beta}$ and ${\tilde\mu_t{(x_t, x_0)}}$ are derived?
It seems to me that exponential term is a 2nd order polynomial term and it doesn't really look like a gaussian in the form of $\frac{(x - \mu)^2}{2\sigma^2}$.
Source:https://lilianweng.github.io/posts/2021-07-11-diffusion-models/#reverse-diffusion-process
