The Gap between Theory and Practice in Function Approximation with Deep Neural Networks-Reference-Cited by-同舟云学术

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The Gap between Theory and Practice in Function Approximation with Deep Neural Networks

Published:2021-01 Issue:2 Volume:3 Page:624-655
ISSN:2577-0187
Container-title:SIAM Journal on Mathematics of Data Science
language:en
Short-container-title:SIAM Journal on Mathematics of Data Science

Author:

Adcock Ben,Dexter Nick^ORCID

Funder

Natural Sciences and Engineering Research Council of Canada

Pacific Institute for the Mathematical Sciences

Simon Fraser University

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Link

https://epubs.siam.org/doi/pdf/10.1137/20M131309X

Reference50 articles.

1. Infinite-Dimensional Compressed Sensing and Function Interpolation

2. Correcting for unknown errors in sparse high-dimensional function approximation

3. Solving inverse problems using data-driven models

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