racc15

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[D] GANs do not have Density estimation abilities in c/machinelearning@academy.garden
[–] racc15@alien.top 1 points 11 months ago

thanks!

there is so much stuff to learn!

[D] GANs do not have Density estimation abilities in c/machinelearning@academy.garden
[–] racc15@alien.top 1 points 11 months ago

but that information is hard to retrieve

that makes sense!

[D] GANs do not have Density estimation abilities in c/machinelearning@academy.garden
[–] racc15@alien.top 1 points 11 months ago (1 children)

In theory, can I use the discriminator of the GAN for this?

It will look at a weird picture and say: this looks fake?

[D] GANs do not have Density estimation abilities in c/machinelearning@academy.garden
[–] racc15@alien.top 1 points 11 months ago (2 children)

thank you for the detailed answer!

​

"GANs indeed learn to generate samples from the data distribution."

So GANs do have estimation capabilities? Can I use the trained discriminator to detect anomalous images? I guess the discriminator should mark them as "fake" due to not being prevalent in the dataset?

1
[D] GANs do not have Density estimation abilities (alien.top)
 

Hello.

I am seeing the GAN specialization course on Coursera by instructor Sharon Zhou.

In one of the lectures, she says that a disadvantage of GANs is that it cannot do density estimation and thus is not useful for anomaly detection. (not sure if you can access it).

In the next video, she says that VAEs don't have this problem.

I am a little confused about this. Could anyone please explain what she means?

As far as I can understand from the lecture, density estimation means learning how probable/frequent particular features are in a dataset. Like, how probable is it that a dog will have droopy ears. Then, we can use this info to detect anomalies if they do not exhibit these features.

But, isn't this exactly what GANs learn? aren't GANs learning to mimic the distribution of the training data?

Also, how is a VAE different in this particular regard?

Could someone please help explain this?

Thank you.

[D] Exclusive: Sam Altman's ouster at OpenAI was precipitated by letter to board about AI breakthrough in c/machinelearning@academy.garden
[–] racc15@alien.top 1 points 11 months ago (1 children)

I am slightly confused.

So, Sam Altman and collegues discovered a very powerful thing called Q*. This will make OpenAI very powerful and will make the board a lot of money.

So, why did this cause the board to fire him?

From the article, it seemed like the board was too afraid of Q* and fired him to stop it being released without proper security features.

Could someone please help clarify this?

Thanks.