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.

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

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 ...

Hinton's motivation for the algorithm is to address some of the shortcomings of standard backpropagation training which requires full knowledge of the computation in the forward pass to compute ...