Activation Functions

# Tanh Activation

Tanh Activation is an activation function used for neural networks:

$$f\left(x\right) = \frac{e^{x} - e^{-x}}{e^{x} + e^{-x}}$$

Historically, the tanh function became preferred over the sigmoid function as it gave better performance for multi-layer neural networks. But it did not solve the vanishing gradient problem that sigmoids suffered, which was tackled more effectively with the introduction of ReLU activations.

Image Source: Junxi Feng

#### Papers

Paper Code Results Date Stars

Time Series 46 7.06%
Language Modelling 36 5.52%
Machine Translation 19 2.91%
Sentiment Analysis 19 2.91%
Text Generation 14 2.15%
Text Classification 14 2.15%
Object Detection 14 2.15%
Speech Recognition 14 2.15%
Time Series Forecasting 13 1.99%

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