The second original Swish paper about e-swish HOT 4 OPEN

@MichaelFomenko always glad to recieve constructive criticism

from e-swish.

He clearly dont understand anything about Deep Learning, he only published this paper to have a published paper for his career.

from e-swish.

Hi, @EliasHasle
I do cite the paper by Ramachandran et al. in my paper already.
wrt to the concern about the beta parameter, it's not the same:

• As you increase the beta in swish, it resembles a ReLU function
• As you increase the beta in e-swish, you augment the properties of the x*sigmoid(x) function.

I hope the image is clarifying!

from e-swish.

Sorry EricAlcaide to tell you the truth, but you clearly don't understand Deep Learning, if you would understand Deep Learning you would know that the Beta in your E-Swish Function is just the Weight of the next Layer. This means that Mathematicaly there is no diverence between your E-Swish and the Swish Function.

from e-swish.