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> everyone knows GANs don't work because they're too unstable Is that a wide spread myth? I thought it’s widely accepted that GAN is really good generating the

> everyone knows GANs don't work because they're too unstable Is that a wide spread myth? I thought it’s widely accepted that GAN is really good generating these artificial pictures (it’s what started DeepFake after all) when you know your model’s “button”. Similar to how this uses GAN since they have a model “boundary condition”. While humans are diverse, we have a set of repeatable features (two legs, two arms, etc). Diffusion models are great because you can control the latent space with something way more generic, like text hence why it’s been so much more mainstream. Edit: actually I might be misremembering, I think Deepfake used VAEs?

gwern 3y ago
It is very widespread. You will see people in this very thread dismissing GANs as fundamentally failed, and hotly objecting to any kind of parity, even if they have to fall back to 'well ok GANs do scale, but they're more complicated'. I also have some representative quotes in my linked draft essay from various papers & DL Twitter discussions. (Another way to put it would be: when was the last time you saw someone besides me asserting that GANs can scale to high-quality general images and are not dramatically inferior to diffusion? I rest my case.)
- ShamelessC 3y ago
  Sounds very important to you that you don’t have to change the premise of your essay or ever admit you’re wrong. No one is dismissive of GAN’s here without justification. They’re fine. They don’t beat diffusion, but they’re fine. You come across as severely, _severely_ biased and reactionary.
  - deleted 3y ago
    [deleted]
- ShamelessC 3y ago
  > Another way to put it would be: when was the last time you saw someone besides me asserting that GANs can scale to high-quality general images and are not dramatically inferior to diffusion? I rest my case. Get off of Twitter, maybe? I don't know but I have seen a ton of work done on large scale GANs. The incentives are pretty fucking obvious - they are faster to use. Of _course_ people want them to work for the same usecases as diffusion. Maybe they will someday! But they aren't currently. You're referencing a zeitgeist that I am not familiar with and therefore come across overly defensive.

gwern 3y ago

It is very widespread. You will see people in this very thread dismissing GANs as fundamentally failed, and hotly objecting to any kind of parity, even if they have to fall back to 'well ok GANs do scale, but they're more complicated'. I also have some representative quotes in my linked draft essay from various papers & DL Twitter discussions. (Another way to put it would be: when was the last time you saw someone besides me asserting that GANs can scale to high-quality general images and are not dramatically inferior to diffusion? I rest my case.)

ShamelessC 3y ago
Sounds very important to you that you don’t have to change the premise of your essay or ever admit you’re wrong. No one is dismissive of GAN’s here without justification. They’re fine. They don’t beat diffusion, but they’re fine. You come across as severely, _severely_ biased and reactionary.
- deleted 3y ago
  [deleted]
ShamelessC 3y ago
> Another way to put it would be: when was the last time you saw someone besides me asserting that GANs can scale to high-quality general images and are not dramatically inferior to diffusion? I rest my case. Get off of Twitter, maybe? I don't know but I have seen a ton of work done on large scale GANs. The incentives are pretty fucking obvious - they are faster to use. Of _course_ people want them to work for the same usecases as diffusion. Maybe they will someday! But they aren't currently. You're referencing a zeitgeist that I am not familiar with and therefore come across overly defensive.