Designed to mimic the brain itself, artificial neural networks use mathematical equations to identify and predict patterns in datasets and images.

We introduce a variational representation of quantum states based on artificial neural networks with a variable number of hidden neurons. A reinforcement-learning scheme we demonstrate is capable of ...

This issue has now been addressed. Li Hang's newly launched book 'Machine Learning Methods (2nd Edition)' dedicates a chapter ...

For this purpose, the researchers use convolutional neural networks (CNNs). This is a special type of artificial neural networks, which is composed of various layers with different tasks.

A team has shown that reinforcement learning -i.e., a neural network that learns the best action to perform at each moment based on a series of rewards- allows autonomous vehicles and underwater ...

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech ...

The development of neural networks to create artificial intelligence in computers was originally inspired by how biological systems work.

Scientists at UCL, Google DeepMind and Intrinsic have developed a powerful new AI algorithm that enables large sets of robotic arms to work together faster and smarter in busy industrial settings, ...

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 ...