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.

This simply means that neural networks running on quantum systems could, potentially, be exponentially more robust than those running on classical systems.

In a separate test, they simply replaced the neural network with qubits. For lightning data, the quantum version outperformed the classical one.

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 ...

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.