Where can I find out about the “Helvetica scenario”?
$begingroup$
From the paper introducing GANs:
It makes sense that collapsing too many $vec{z}$-values to a single $vec{x}$-value will cause problems. However, I was a bit confused as to how training $G$ for a shorter amount of time before running $D$ can fix it. But when I googled "Helvetica scenario", all I could find were references to a parody show called Look Around You.
Since it seems like this is an actual thing, not just a parody—where can I find out more about it, and how it can be prevented? And why is it called "the Helvetica scenario"?
machine-learning neural-network gan generative-models
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$endgroup$
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$begingroup$
From the paper introducing GANs:
It makes sense that collapsing too many $vec{z}$-values to a single $vec{x}$-value will cause problems. However, I was a bit confused as to how training $G$ for a shorter amount of time before running $D$ can fix it. But when I googled "Helvetica scenario", all I could find were references to a parody show called Look Around You.
Since it seems like this is an actual thing, not just a parody—where can I find out more about it, and how it can be prevented? And why is it called "the Helvetica scenario"?
machine-learning neural-network gan generative-models
New contributor
$endgroup$
add a comment |
$begingroup$
From the paper introducing GANs:
It makes sense that collapsing too many $vec{z}$-values to a single $vec{x}$-value will cause problems. However, I was a bit confused as to how training $G$ for a shorter amount of time before running $D$ can fix it. But when I googled "Helvetica scenario", all I could find were references to a parody show called Look Around You.
Since it seems like this is an actual thing, not just a parody—where can I find out more about it, and how it can be prevented? And why is it called "the Helvetica scenario"?
machine-learning neural-network gan generative-models
New contributor
$endgroup$
From the paper introducing GANs:
It makes sense that collapsing too many $vec{z}$-values to a single $vec{x}$-value will cause problems. However, I was a bit confused as to how training $G$ for a shorter amount of time before running $D$ can fix it. But when I googled "Helvetica scenario", all I could find were references to a parody show called Look Around You.
Since it seems like this is an actual thing, not just a parody—where can I find out more about it, and how it can be prevented? And why is it called "the Helvetica scenario"?
machine-learning neural-network gan generative-models
machine-learning neural-network gan generative-models
New contributor
New contributor
New contributor
asked 49 mins ago
DraconisDraconis
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