The Probability distribution of an Adversarial Autoencoder
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As I want to gain more knowledge about Adversarial Autoencoders, I'm reading this series on "towardsDataScience" about the subject. Now I do have a decent understanding of statistics (at least about all the terminology). But in this post the author writes the following:
our main aim in this part will be to force the encoder output to match a given prior distribution
Now I'm having issues with how to interpret what exactly the prior distribution is?
Is it an encoded version of all the training samples that we use for "training the encoder"?
Please help me clear this out!
machine-learning tensorflow data autoencoder
asked 2 days ago
FritskeeFritskee
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add a comment |
$begingroup$
As I want to gain more knowledge about Adversarial Autoencoders, I'm reading this series on "towardsDataScience" about the subject. Now I do have a decent understanding of statistics (at least about all the terminology). But in this post the author writes the following:
our main aim in this part will be to force the encoder output to match a given prior distribution
Now I'm having issues with how to interpret what exactly the prior distribution is?
Is it an encoded version of all the training samples that we use for "training the encoder"?
Please help me clear this out!
machine-learning tensorflow data autoencoder
asked 2 days ago
FritskeeFritskee
1
New contributor
Fritskee is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
As I want to gain more knowledge about Adversarial Autoencoders, I'm reading this series on "towardsDataScience" about the subject. Now I do have a decent understanding of statistics (at least about all the terminology). But in this post the author writes the following:
our main aim in this part will be to force the encoder output to match a given prior distribution
Now I'm having issues with how to interpret what exactly the prior distribution is?
Is it an encoded version of all the training samples that we use for "training the encoder"?
Please help me clear this out!
machine-learning tensorflow data autoencoder
asked 2 days ago
FritskeeFritskee
1
New contributor
Fritskee is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
As I want to gain more knowledge about Adversarial Autoencoders, I'm reading this series on "towardsDataScience" about the subject. Now I do have a decent understanding of statistics (at least about all the terminology). But in this post the author writes the following:
our main aim in this part will be to force the encoder output to match a given prior distribution
Now I'm having issues with how to interpret what exactly the prior distribution is?
Is it an encoded version of all the training samples that we use for "training the encoder"?
Please help me clear this out!
machine-learning tensorflow data autoencoder
machine-learning tensorflow data autoencoder
asked 2 days ago
FritskeeFritskee
1
New contributor
Fritskee is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 days ago
FritskeeFritskee
1
New contributor
Fritskee is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 days ago
FritskeeFritskee
1
New contributor
Fritskee is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 days ago
FritskeeFritskee
1
asked 2 days ago
FritskeeFritskee
1
1
New contributor
Fritskee is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Fritskee is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Fritskee is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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