Learning to Rank Tensor Network Contraction Plans for GPU-Accelerated Quantum Circuit Simulation
A learning-to-rank framework for selecting efficient contraction plans before executing them and supporting Learning to Rank as a practical way to reduce contraction-plan search, while showing that performance remains partly backend dependent.
Alfred M. Pastor, Maribel Castillo, José M. Badía
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