Hybrid Quantum: Classical Architectures For Machine Learning

As you begin your hybrid quantum approach, here are the advantages, use cases and limitations to keep in mind.

Adaptive method helps light-based quantum processors act more like neural networks

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...

Interpretable machine learning to accelerate nanocatalyst discovery

A fast and accurate surrogate model screens over 10,000 possible metal-oxide supports for a platinum nanocatalyst to prevent sintering under high temperatures.
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Displaying items by tag: Quantum Machine Learning

The project will build upon CSIRO’s expertise in the field of QML to develop new and innovative QML models. QML has the potential to offer enhanced reliability, training speed-up and unique feature ...

Nvidia's Quiet Move Into Quantum Computing Could Reshape the Next Frontier of AI

Quantum computing is still years away, but Nvidia just built the bridge that will bring it closer -- a quiet integration of AI, GPUs, and patience that could shorten the wait for the next computing ...