The Exponential Linear Squashing Activation Function, or ELiSH, is an activation function used for neural networks. It shares common properties with Swish, being made up of an ELU and a Sigmoid:
$$f\left(x\right) = \frac{x}{1+e^{x}} \text{ if } x \geq 0 $$ $$f\left(x\right) = \frac{e^{x}  1}{1+e^{x}} \text{ if } x < 0 $$
The Sigmoid part of ELiSH improves information flow, while the linear parts solve issues of vanishing gradients.
Source: The Quest for the Golden Activation FunctionPaper  Code  Results  Date  Stars 

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