Year: 2018
Type: preprint
Abstract: In this paper we introduce new bounds on the approximation of functions in deep networks and in doing so introduce some new deep network architectures for function approximation. These results give some theoretical insight into the success of autoencoders and ResNets.
Source: arXiv (Cornell University)
Authors: McCane, Brendan, Szymanski, Lech
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2789470915