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Simon Callum Marshall

2 accepted papers

2026

Quantum machine learning advantages beyond hardness of evaluation

ICLR 2026poster

Recent years have seen rigorous proofs of quantum advantages in machine learning, particularly when data is labeled by cryptographic or inherently quantum functions. These results typically rely on the infeasibility of classical polynomial-sized circuits to evaluate the true labeling function. While…

Cited by 0SourceScholar
2021

Parametrized Quantum Policies for Reinforcement Learning

NeurIPS 2021poster

With the advent of real-world quantum computing, the idea that parametrized quantum computations can be used as hypothesis families in a quantum-classical machine learning system is gaining increasing traction. Such hybrid systems have already shown the potential to tackle real-world tasks in superv…

Cited by 184SourcePDFScholar