arXiv Machine Learning July 23, 2026 By Armin Ahmadkhaniha, Jake Doliskani

Edge-Local and Qubit-Efficient Quantum Graph Learning for the NISQ Era

Read the original on arXiv Machine Learning →

arXiv:2602. 16018v2 Announce Type: replace-cross Abstract: Graph neural networks (GNNs) are a powerful framework for learning representations from graph-structured data, but their direct implementation on near-term quantum hardware remains challenging due to circuit depth, multi-qubit interactions, and qubit scalability constraints.

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