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Integrate previous version of asdfhjkl
directly into Laplace
#238
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aleximmer
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Thanks for the progress!
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Thanks, sounds good to me. I think |
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First version integrating the old asdfghjkl into Laplace directly. This allows to have it alongside the latest asdl and further integrate existing extensions, such as end-to-end differentiability and support for other loss functions. This version does not change any behavior and only integrates functions of asdfghjkl that are actually used. The only exception to this is
kernel.py
, which is currently not yet used but will be worth integrating.Points to discuss:
asdfghjkl_src
?asdfghjkl
can be default by enabling regression?asdfghjkl
becomes default, what is a sensible way to integrate it? I think we could havecurvature/asd
for the core utilities and merge the interfaces/default backends incurvature.py
withasdfghjkl.py
, deprecate theAsdfghjklXYZ
classes and just go withGGN, EF, Hessian
for them.