# Parameter of Conditional Gaussian Distribution

I'd like to understand how to determine the parameter of conditional gaussian distribution. Following is the network architecture of VUNET which learns the conditional gaussian distribution $q(z|x, \hat y)$ of appearance of human($z$) upon given two conditional inputs skeleton of body pose and groundTruth image($x$) of 128x128 resolution image

I don't understand how $2\times2\times256$ vector and $1\times1$ vector can characterize $q(z|x, \hat y)$. Any advice to understand this point clearly?