AI’s Memorization Crisis

O n Tuesday, researchers at Stanford and Yale revealed something that AI companies would prefer to keep hidden. Four popular ...
EurekAlert!

SEOULTECH researchers develop VFF-Net, a revolutionary alternative to backpropagation that transforms AI training

VFF-Net introduces three new methodologies: label-wise noise labelling (LWNL), cosine similarity-based contrastive loss (CSCL), and layer grouping (LG), addressing the challenges of applying a forward ...
Hosted on MSN

Backpropagation In Neural Networks — Full Derivation Step-By-Step

Understand the Maths behind Backpropagation in Neural Networks. In this video, we will derive the equations for the Back Propagation in Neural Networks. In this video, we are using using binary ...
Hosted on MSN

Backpropagation From Scratch in Python

Build your own backpropagation algorithm from scratch using Python — perfect for hands-on learners! Attorney reveals what Kirk shooting suspect told roommate via text: ‘I’d hope to keep this secret’ ...
EurekAlert!

Not so simple machines: Cracking the code for materials that can learn

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. The ...
Semiconductor Engineering

Backpropagation Algorithm On Neuromorphic Spiking HW (U. Of Zurich, ETH Zurich, LANL)

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 ...
IEEE

Prediction of Electricity load structure and evolution trend of distribution network under the background of Accelerated Electricity Substitution based on Genetic Algorithm ...

Abstract: Compared to other primary energy sources, electricity is more convenient, safe, and clean, and has significant advantages in terms of energy conversion efficiency at the consumption side. In ...
Frontiers

Back-Propagation Learning in Deep Spike-By-Spike Networks

Artificial neural networks (ANNs) are important building blocks in technical applications. They rely on noiseless continuous signals in stark contrast to the discrete action potentials stochastically ...