<ul><li>The Multi-Chip Ensemble VQC framework, developed by researchers like Junghoon Justin Park and others, partitions quantum computations across multiple quantum chips for scalability and noise resilience.</li><li>Key benefits of this framework include its validation with standard datasets and robustness under realistic noise models, showcasing potential for practical Quantum Machine Learning (QML) applications.</li><li>The framework aligns with industry efforts for scalable quantum architectures, such as Rigetti Computing's multi-chip processor and MIT's modular hardware platform, highlighting the trend towards modular and scalable quantum computing solutions.</li><li>The Multi-Chip Ensemble VQC framework is a significant advancement in practical and scalable Quantum Machine Learning, offering a modular approach that addresses challenges of NISQ devices, positioning it as a promising solution for future QML applications.</li></ul>

Advancing Quantum Machine Learning with Multi-Chip Ensemble Architectures

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