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Folding over Neural Networks. (arXiv:2207.01090v1 [cs.PL])
July 5, 2022, 1:10 a.m. | Minh Nguyen, Nicolas Wu
cs.LG updates on arXiv.org arxiv.org
Neural networks are typically represented as data structures that are
traversed either through iteration or by manual chaining of method calls.
However, a deeper analysis reveals that structured recursion can be used
instead, so that traversal is directed by the structure of the network itself.
This paper shows how such an approach can be realised in Haskell, by encoding
neural networks as recursive data types, and then their training as recursion
scheme patterns. In turn, we promote a coherent implementation …
More from arxiv.org / cs.LG updates on arXiv.org
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