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Same model for classification as well as generating samples #3

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Ektagavas opened this issue Sep 10, 2021 · 1 comment
Open

Same model for classification as well as generating samples #3

Ektagavas opened this issue Sep 10, 2021 · 1 comment

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@Ektagavas
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Hey, thank you for sharing the code. It's great!
I had one query. I have trained a Mintnet model for classification on CIFAR10. Can I use this same model for generating new samples i.e as a generative model (with some code modifications, of course)? If yes, can you suggest what part of the code needs to be changed?
As far as I understood, currently, density estimation and classification experiments are run independently, but I want to make changes to achieve the above use-case.
Thanks in advance!

@yang-song
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Hello, I don't think it's easy to convert a classifier to a generative model. For image generation, you will need to first have the logits layer of a MintNet classifier and then compute the inverse. The first step is non-trivial.

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