Search Results for author: Simon Tavener

Found 1 papers, 0 papers with code

Rethinking the Relationship between Recurrent and Non-Recurrent Neural Networks: A Study in Sparsity

no code implementations1 Apr 2024 Quincy Hershey, Randy Paffenroth, Harsh Pathak, Simon Tavener

In particular, RNNs are known to be Turing complete, and therefore capable of representing any computable function (such as any other types of NNs), but herein we argue that the relationship runs deeper and is more practical than this.

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