TRANSFER LEARNING IN HYBRID CLASSICAL-QUANTUM NEURAL NETWORKS

Transfer learning in hybrid classical-quantum neural networks

We extend the concept of transfer learning, widely applied in modern machine learning algorithms, Collections to the emerging context of hybrid neural networks composed of classical and quantum elements.We propose different implementations of hybrid transfer learning, but we focus mainly on the paradigm in which a pre-trained classical network is m

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A nonparametric approach for detecting urban polycentric spatial structure in China using remote sensing nighttime light and point of interest data

Effectively identifying urban polycentric spatial structure (UPSS) is essential for data-driven evaluation of urban performance, and it serves as a scientific basis for urban spatial planning.However, existing identification methods have limitations such as subjectivity, poor spatial continuity, and a narrow application scale.Thus, from a morpholog

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