In this code, I have explored the sigmoid function, a vital tool in machine learning and neural networks, by visualizing how it behaves with different threshold values. First, the sigmoid function is ...

To develop a python code that creates a simple feed-forward neural networks or perception with the Sigmoid activation function. The neuron has to be trained such that it can predict the correct output ...

This paper studies the influences of variable scales and sigmoid activation functions on the performances of multi-layer perceptrons. Generally speaking, it is not certainly suitable to normalize the ...

The researchers identify that the main challenge with naive sigmoid attention (SigmoidAttn) lies in the large initial attention norms. To address this, they propose several solutions and make ...

We demonstrate a programmable analog opto-electronic (OE) circuit that can be configured to provide a range of nonlinear activation functions for incoherent neuromorphic photonic circuits at up to 10 ...