Figure illustrating the architecture of the quantum convolutional neural networks developed by the researchers. Credit: Cong, Choi & Lukin.

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 ...

WiMi's quantum algorithm provides exponential speedup in both stages, enabling neural networks to achieve convergence in significantly less time.

They are developing a Quantum Convolutional Neural Network (QCNN) architecture to enhance the performance of traditional computer vision tasks using quantum mechanics principles.

I wrote about quantum computing and a version of deep learning that was related: a “quantum walk neural network.” Now, quantum computing is beginning to emerge.

For example, quantum computing, an area Intel has invested more than $50 million in to research, could advance further with a more efficient approach to testing highly complex quantum systems. The ...

Neural networks are likely to increase the scope of problems that can be solved, says Jay Gambetta, who leads IBM’s quantum computing efforts, but he’s unconvinced they’ll solve the hardest ...