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cs.LG2025
Minimum width for universal approximation using squashable activation functions
Jonghyun Shin, Namjun Kim, Geonho Hwang +1
The exact minimum width that allows for universal approximation of unbounded-depth networks is known only for ReLU and its variants. In this work, we study the minimum width of net…
cs.LG2023★ 1 cited
Minimum width for universal approximation using ReLU networks on compact domain
Namjun Kim, Chanho Min, Sejun Park
It has been shown that deep neural networks of a large enough width are universal approximators but they are not if the width is too small. There were several attempts to character…