This article describes the backpropagation algorithm, a basic neural network, and its implementation on a Lego Roverbot with Java.

Build your own backpropagation algorithm from scratch using Python — perfect for hands-on learners!

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 early December, dozens of alternatives to traditional backpropagation were proposed during a workshop at the NeurIPS 2020 conference, which took place virtually. Some leveraged hardware like ...

Obtaining the gradient of what's known as the loss function is an essential step to establish the backpropagation algorithm developed by University of Michigan researchers to train a material ...

Neural networks made from photonic chips can be trained using on-chip backpropagation – the most widely used approach to training neural networks, according to a new study. The findings pave the ...

Here, we propose a hardware implementation of the backpropagation algorithm that progressively updates each layer using in situ stochastic gradient descent, avoiding this storage requirement.

Back-propagation is by far the most common neural-network training algorithm, but by no means is it the only algorithm. Important alternatives include real-valued genetic algorithm training and ...