Swish

Swish is an activation function used in neural networks, which helps them make decisions. It’s similar to the more common ReLU function but has a smoother curve. Specifically, Swish is defined mathematically as \( f(x) = x \cdot \text{sigmoid}(x) \), where the sigmoid function squashes values to a range between 0 and 1. This allows the function to output values that can be both positive and negative, which helps the network learn more complex patterns. Many researchers find that using Swish can improve the performance of deep learning models compared to traditional functions like ReLU.