Label embedding in Auxiliary Classifier GANs
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In Auxiliary Classifier GAN the generator takes two inputs, 1. one hot encoding of the labels, and 2. noise vector. But in the implementation of the GAN (e.g.:) some embedding is used, I think it is to convert the sparse one-hot-encoded vectors into a dense form. But what I dont understand is, then this embedded labels are then multiplied with the noise vector and rest of the layers are based on this multiplied input. My questions are:
- Why these two vectors are multiplied instead of concatenation?
- Lets assume that I have to give another input, y (another one-hot representation), in addition to the labels, and noise. In that case can I still multiply the embedded labels, embedded y and noise all together and give as the input to the rest of the layers?
machine-learning convnet pytorch gan
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user570593user570593
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$begingroup$
In Auxiliary Classifier GAN the generator takes two inputs, 1. one hot encoding of the labels, and 2. noise vector. But in the implementation of the GAN (e.g.:) some embedding is used, I think it is to convert the sparse one-hot-encoded vectors into a dense form. But what I dont understand is, then this embedded labels are then multiplied with the noise vector and rest of the layers are based on this multiplied input. My questions are:
- Why these two vectors are multiplied instead of concatenation?
- Lets assume that I have to give another input, y (another one-hot representation), in addition to the labels, and noise. In that case can I still multiply the embedded labels, embedded y and noise all together and give as the input to the rest of the layers?
machine-learning convnet pytorch gan
asked 1 min ago
user570593user570593
1011
New contributor
user570593 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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add a comment |
$begingroup$
In Auxiliary Classifier GAN the generator takes two inputs, 1. one hot encoding of the labels, and 2. noise vector. But in the implementation of the GAN (e.g.:) some embedding is used, I think it is to convert the sparse one-hot-encoded vectors into a dense form. But what I dont understand is, then this embedded labels are then multiplied with the noise vector and rest of the layers are based on this multiplied input. My questions are:
- Why these two vectors are multiplied instead of concatenation?
- Lets assume that I have to give another input, y (another one-hot representation), in addition to the labels, and noise. In that case can I still multiply the embedded labels, embedded y and noise all together and give as the input to the rest of the layers?
machine-learning convnet pytorch gan
asked 1 min ago
user570593user570593
1011
New contributor
user570593 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
In Auxiliary Classifier GAN the generator takes two inputs, 1. one hot encoding of the labels, and 2. noise vector. But in the implementation of the GAN (e.g.:) some embedding is used, I think it is to convert the sparse one-hot-encoded vectors into a dense form. But what I dont understand is, then this embedded labels are then multiplied with the noise vector and rest of the layers are based on this multiplied input. My questions are:
- Why these two vectors are multiplied instead of concatenation?
- Lets assume that I have to give another input, y (another one-hot representation), in addition to the labels, and noise. In that case can I still multiply the embedded labels, embedded y and noise all together and give as the input to the rest of the layers?
machine-learning convnet pytorch gan
machine-learning convnet pytorch gan
asked 1 min ago
user570593user570593
1011
New contributor
user570593 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 1 min ago
user570593user570593
1011
New contributor
user570593 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 1 min ago
user570593user570593
1011
New contributor
user570593 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 1 min ago
user570593user570593
1011
asked 1 min ago
user570593user570593
1011
1011
New contributor
user570593 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
user570593 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
user570593 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
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