2 papers
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
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…