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github-actions[bot] committed May 30, 2024
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* proofs as types.

We can consider the type of types, UU the universe of universes.
The types can related in paths of type level or dependent type programming
in haskell for example.
We can convert unimath proofs to ocaml and haskell via metacoq extractions.
we can train a detailed model to reverse this extraction,
a automatic reverse extractor that is trained on the extraction.
We can use this method to convert values from trained model weights
using symbolic regression and program generation.
These generated programs can be apprehended as types.
the types can be bound into the proof engine.
this shows the connection of a value learned by a neural network
and a values held in the proof engine as a constructed proof in metacoq.
That means we can also train a neural network to reverse this process.
we can go from unimath proofs to templates to create preptrained neural networks and back.

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