This repository contains an experimental PyTorch implementation exploring the NoProp algorithm, presented in the paper "NOPROP: TRAINING NEURAL NETWORKS WITHOUT BACK-PROPAGATION OR FORWARD-PROPAGATION ...

This study presents valuable computational findings on the neural basis of learning new motor memories without interfering with previously learned behaviours using recurrent neural networks. The ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Several significant research studies related to Preventing Phishing Attacks for Cyber Threat Mitigation have been reviewed ...

Dana Heitz reviews a criminal case out of Arizona involving AI-generated evidence. She sets out some ethical considerations for its future use—an issue of interest to attorneys and courts in New ...

Confused by neural networks? Break it down step-by-step as we walk through forward propagation using Python—perfect for beginners and curious coders alike!

Detailed explanation and hands-on Python implementation of dropout from scratch. #Dropout #PythonAI #NeuralNetworks Donald Trump's remarks about Putin leave Russian state TV stunned Which Berry ...

Compatibility optimization of the traditional Chinese medicines ‘Eczema mixture’ based on back-propagation artificial neural network and non-dominated sorting genetic algorithm ...

This study introduces PROFIS, a new generative model capable of the design of structurally novel and target-focused compound libraries. The model relies on a recurrent neural network that was trained ...

Robotic arms are increasingly being utilized in agriculture, where agility and precise movement are essential for their effective implementation. To enhance the performance of these manipulators, many ...