Integrated quantum computing company Quantinuum Ltd. today unveiled new open-source software tools designed to accelerate ...

Quantum machine learning is a highly promising application for quantum computing. The hybrid quantum-classical convolutional neural networks (QCCNN) employs parameter quantum circuit to enhance ...

A neural network implementation can be a nice addition to a Python programmer's skill set. If you're new to Python, examining a neural network implementation is a great way to learn the language.

Italian researchers recently developed the first functioning quantum neural network by running a special algorithm on an actual quantum computer. The team, lead by Francesco Tacchino of the ...

Quantum resources for artificial intelligence Memristors are thought to be valuable in neural networks, which typically require large amounts of training data to operate effectively. An architecture ...

The practical assessment of quantum computing by tech leaders requires knowledge of how quantum computing differs from classical computing systems.

For example, when using the quantum processor to reconstruct lightning data, they found it did a better job at lower altitudes but was generally comparable to the classical neural network.

Combining quantum computing with neural networks could produce AI that can make very complex decisions quickly.

Data scientist Dr. James McCaffrey begins a series on presenting and explaining the most common modern techniques used for neural networks, for which over the past couple of years there have been many ...