A new model of learning centers on bursts of neural activity that act as teaching signals — approximating backpropagation, the algorithm behind learning in AI.

In this video, we will understand Backpropagation in RNN. It is also called Backpropagation through time, as here we are ...

Understand the Maths behind Backpropagation in Neural Networks. In this video, we will derive the equations for the Back ...

Backpropagation is not limited to function derivatives. Any algorithm that effectively takes the loss function and applies gradual, positive changes back through the network is valid.

The Forward-Forward algorithm (FF) is comparable in speed to backpropagation but has the advantage that it can be used when the precise details of the forward computation are unknown.

The most common technique used to train neural networks is the back-propagation algorithm. Back propagation requires a value for a parameter called the learning rate. The effectiveness of back ...

A new technical paper titled “The backpropagation algorithm implemented on spiking neuromorphic hardware” was published by University of Zurich, ETH Zurich, Los Alamos National Laboratory, Royal ...

The algorithm, called backpropagation, was the spark that fired up the current revolution of deep learning as the de facto machine learning behemoth. At its core, “backprop” is an extremely effective ...