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Computation of denoising posterior precision matrix in JAC method (score_fn_iid)

Open touronc opened this issue 8 months ago • 1 comments

I am working with the JAC score estimation (for i.i.d. data) inspired by the paper "Diffusion posterior sampling for simulaton-based inference in tall data settings" from Linhart J. et al (algorithm 2).

In the estimation of the marginal denoising posterior precision matrix, why is there an addition between the 2 terms ? Shouldn't it be a multiplication instead ?

Here is the link to the specific line of the function : (https://github.com/sbi-dev/sbi/blob/dac03dbdcda3760e3de6d843d0ea4e4b644d8dc0/sbi/inference/potentials/score_fn_iid.py#L727)

Thanks !

touronc avatar Apr 10 '25 08:04 touronc

Thanks for raising this @touronc ! @manuelgloeckler any thoughts?

janfb avatar Apr 10 '25 08:04 janfb

Thanks for checking I think you are right, this should be a multiplication, good catch!

Will test and adjust.

manuelgloeckler avatar Aug 13 '25 10:08 manuelgloeckler