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Just having heard lately about BNNs (wow, ANNs and CNNs are clear; now there's a B? What's that? Ahh, Bayesian ;-)) and quickly getting their main idea and focus, that is, weights not being pure static numbers anymore, but instead described by a distribution function, allowing the net to be "uncertain" about its answers (for more about BNNs, see, for example, this post, or, if you want to know a lot about them, check out this introduction and survey),

I'm now curious about any practical examples of where BNNs are used nowadays, maybe even more successful than other (deep learning) alternatives?

Thanks to nbro's comment here, pointing out that asking this question is not unknowingly, but relevant.

nbro
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Mathy
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  • Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. – Community Jun 24 '22 at 00:24
  • https://arxiv.org/pdf/2002.00269.pdf – Daniel Jun 24 '22 at 03:45
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    @Community I am questioning today's practicality of BNNs and asking (see tags) for state-of-the-art and/or references. I think it's clear what I am asking and how an adequate answer would look like. Please correct me if I am mistaken here. – Mathy Jun 27 '22 at 06:36
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    @dangom I skimmed that article but I honestly could not find any real value about my question in it. It's morge like the introduction and survey I linked above; but not about its daily use. – Mathy Jun 27 '22 at 06:41

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