Understand what activation functions are and why they’re essential in deep learning! This beginner-friendly explanation ...

A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive ...

Although neural networks have been studied for decades, over the past couple of years there have been many small but significant changes in the default techniques used. For example, ReLU (rectified ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...

Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs ...

UCLA researchers demonstrate diffractive optical processors as universal nonlinear function approximators using linear ...