Build your own backpropagation algorithm from scratch using Python — perfect for hands-on learners! An Air India Boeing 787 flying to London with over 240 people on board crashed shortly after ...

The backpropagation algorithm, which is based on the derivation of a cost function, is used to optimize the connecting weights, but neural networks have a lot of other knobs to turn.

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 ...

Back Propagation is a common method of training artificial neural networks so as to minimize objective function. This paper describes the implementation of back propagation algorithm.

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.

AlphaTensor has already identified a new algorithm with which matrix multiplications can be carried out faster than before, as the research team explains in a paper published in the magazine Nature.

Neural networks using the backpropagation algorithm were biologically “unrealistic in almost every respect” he said. For one thing, neurons mostly send information in one direction.