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quant-ph2026
Information-Theoretic Limits of Quantum Learning via Data Compression
Armando Angrisani, Brian Coyle, Elham Kashefi
Understanding the power of quantum data in machine learning is central to many proposed applications of quantum technologies. While access to quantum data can offer exponential adv…
quant-ph2025
The Born Ultimatum: Conditions for Classical Surrogation of Quantum Generative Models with Correlators
Mario Herrero-Gonzalez, Brian Coyle, Kieran McDowall +4
Quantum Circuit Born Machines (QCBMs) are powerful quantum generative models that sample according to the Born rule, with complexity-theoretic evidence suggesting potential quantum…