Conformalized Quantum DeepONet Ensembles: Towards Scalable Operator Learning with Distribution-Free Guarantees
These results connect resource-aware scalability analysis with finite-sample uncertainty guarantees for quantum operator learning, and explore hybrid classical-quantum architectures and superposed execution to manage ensemble runtime and hardware requirements.
Purav Matlia, Christian Moya, Guang Lin
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