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Trying to understand "Topos and Stacks of Deep Neural Networks"


alex
 alex
(@alex)
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This thread is about trying to understand preprint https://arxiv.org/abs/2106.14587 and its accompanying mathematical exposition chapter https://www.cambridge.org/core/books/abs/mathematics-for-future-computing-and-communications/mathematics-for-ai-categories-toposes-types/F75B023A3C42FAB5D4F186376216FC76

There is similar thread in nforum https://nforum.ncatlab.org/discussion/13133/understanding-preprint-topos-and-stacks-of-deep-neural-networks/#Item_0 and some Stackexchange questions.

The latest Stack question has been created this evening https://math.stackexchange.com/questions/4381378/how-omega-x-is-related-to-omega-as-subobject-classifier-trying-to-under about subobject classifiers. I hope that here or in NForum or StackExchange we can discuss these questions and help each other to get some understanding about this work.

I am a little bit shy to connect with the original authors, because I am beginner and maybe my questions are not at the level to spend time of serious researchers.


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jcbelfiore
(@jcbelfiore)
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@alex and also @tomR

Please find some explanations in the file which is attached. 

Best Regards

Jean-Claude Belfiore and Daniel Bennequin


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