Combining newer neural networks with older AI systems could be the secret to building an AI to match or surpass human ...

Past psychology and behavioral science studies have identified various ways in which people's acquisition of new knowledge ...

Blending ‘old-fashioned’ logic systems with the neural networks that power large language models is one of the hottest trends ...

Information Theory Meets Deep Neural Networks: Theory and Applications. The previous volume can be viewed here: Volume I Deep Neural Networks (DNNs) have become one of the most popular research ...

The Tomorrow’s Quants series explores the skills needed by new quant recruits, drawing on a survey of 39 employers, and six ...

Overview Books provide a deeper understanding of AI concepts beyond running code or tutorials.Hands-on examples and practical ...

The current machine_learning directory in TheAlgorithms/Python lacks implementations of neural network optimizers, which are fundamental to training deep learning models effectively. To fill this gap ...

The title of this article was erroneously given as: Paired competing neurons improving STDP supervised local learning in Spiking Neural Networks. The correct title of the article is: Paired competing ...

MicroCloud Hologram Inc. has announced the creation of a noise-resistant Deep Quantum Neural Network (DQNN) architecture, which aims to advance quantum computing and enhance the efficiency of quantum ...

This repository contains my implementation of a feed-forward neural network classifier in Python and Keras, trained on the Fashion-MNIST dataset. It closely follows the tutorial by The Clever ...