Dynamical simulation via quantum machine learning with provable generalization

no code implementations • 21 Apr 2022 • Joe Gibbs, Zoë Holmes, Matthias C. Caro, Nicholas Ezzell, Hsin-Yuan Huang, Lukasz Cincio, Andrew T. Sornborger, Patrick J. Coles

Much attention has been paid to dynamical simulation and quantum machine learning (QML) independently as applications for quantum advantage, while the possibility of using QML to enhance dynamical simulations has not been thoroughly investigated.

BIG-bench Machine Learning Generalization Bounds +1

Out-of-distribution generalization for learning quantum dynamics

no code implementations • 21 Apr 2022 • Matthias C. Caro, Hsin-Yuan Huang, Nicholas Ezzell, Joe Gibbs, Andrew T. Sornborger, Lukasz Cincio, Patrick J. Coles, Zoë Holmes

However, there are currently no results on out-of-distribution generalization in QML, where we require a trained model to perform well even on data drawn from a different distribution to the training distribution.

Generalization Bounds Out-of-Distribution Generalization +1