Covers quantum generative models for advanced QML applications
Includes case studies and practical examples for real-world insights
Explains both theoretical formulations and hybrid quantum-classical workflows
Discusses error mitigation and hardware benchmarks for near-term quantum computing
Accessible reference text suitable for students and researchers
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Report copyright infringement by Kathleen E. Hamilton (Author), Andrea Delgado (Author)
The scope of the book spans from the fundamental postulates of quantum mechanics and quantum algorithms that underpin QML, to advanced topics including variational quantum algorithms, quantum neural networks, and quantum generative models. It covers both