f-dangel / backpack

BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.

Home Page:https://backpack.pt/

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Feature for backpack on VAEs

shubham0704 opened this issue · comments

Hi All!
I want to contribute to backpack with an implementation that works for VAEs. Please let me know if anyone else is working on this or I can carry out this task. I need to do this for my own research and figured you might also want this feature. Thanks a lot for building this amazing library!

Hi,

sounds like a feature that would be useful for others! I am not aware of anyone working on this.

Disclaimer: I don't have much expertise on VAEs. So its hard for me to foresee potential design problems in BackPACK that might complicate realizing this feature, and to provide informed feedback. If you want though, we can have a virtual meeting to talk details.

Felix

Got it! My email for correspondence is shubham.bhardwaj@utexas.edu
Currently, I am looking to see how to add custom loss function and then going for checking how can we incorporate models using torch.distributions package. What I can do initially is to create a colab notebook with the fork of this repository with modifications that would enable me to have a better discussion with you on where I am stuck.