Parameter of Conditional Gaussian Distribution
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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 $2times2times256$ vector and
$1times1$ vector can characterize $q(z|x, hat y)$. Any advice to understand this point clearly?
normal-distribution conditional-probability
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up vote
0
down vote
favorite
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 $2times2times256$ vector and
$1times1$ vector can characterize $q(z|x, hat y)$. Any advice to understand this point clearly?
normal-distribution conditional-probability
add a comment |Â
up vote
0
down vote
favorite
up vote
0
down vote
favorite
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 $2times2times256$ vector and
$1times1$ vector can characterize $q(z|x, hat y)$. Any advice to understand this point clearly?
normal-distribution conditional-probability
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 $2times2times256$ vector and
$1times1$ vector can characterize $q(z|x, hat y)$. Any advice to understand this point clearly?
normal-distribution conditional-probability
normal-distribution conditional-probability
asked Aug 31 at 2:06
Beverlie
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1,078318
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