GitHub

Rabia-Akhtr/Back-propagation-Machine-Learning-Tutorial

Backpropagation is a supervised learning algorithm used to optimize Artificial Neural Networks (ANNs). This project demonstrates the working of Backpropagation and its application in training neural ...
EurekAlert!

Backpropagation training achieved in photonic neural network

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 way ...
Diginomica

Generative AI needs better context - you can't talk about Large Language Models without reverse neural networks and backpropagation

The hype over Large Language Models (LLMs) has reached a fever pitch. But how much of the hype is justified? We can't answer that without some straight talk - and some definitions. Time for a ...
IEEE

ELM-DeepONets: Backpropagation-Free Training of Deep Operator Networks via Extreme Learning Machines

Abstract: Deep Operator Networks (DeepONets) are among the most prominent frameworks for operator learning, grounded in the universal approximation theorem for operators. However, training DeepONets ...
GitHub

bxcn148/Homework-1-Backpropagation-Deep-Learning-Solution

To answer questions in this part, you need some basic knowledge of linear algebra and matrix calculus. Also, you need to follow the instructions: Every vector is treated as column vector. You need to ...