Demystifying GELU
Last Updated on July 25, 2023 by Editorial Team
Author(s): Konstantinos Poulinakis
Originally published on Towards AI.
Python Code for GELU activation function
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In this tutorial we aim to comprehensively explain how Gaussian Error Linear Unit, GELU activation works.
Can we combine regularization and activation functions? In 2016 a paper from authors Dan Hendrycks and Kevin Gimpel came out. Since then, the paper now has been updated 4 times. The authors introduced a new activation function, the Gaussian Error Linear Unit, GELU.
The motivation behind GELU activation is to bridge stochastic regularizers, such as dropout, with non-linearities, i.e., activation functions.
Dropout regularization stochastically multiplies a neuron’s inputs with 0, randomly… Read the full blog for free on Medium.
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