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Jake Doliskani

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#machine learning Feb 2026

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

This work introduces a hybrid quantum graph learning architecture designed explicitly for unsupervised learning in the noisy intermediate-scale quantum (NISQ) regime that combines a variational quantum feature extraction layer with an edge-local and qubit-efficient quantum message-passing mechanism inspired by the Quantum Alternating Operator Ansatz (QAOA) framework.

Armin Ahmadkhaniha, Jake Doliskani · arXiv.org · 0 citations

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