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Physics-Informed Bayesian Optimization of Variational Quantum Circuits Kim A. Nicoli 1,2,3 Christopher J. Anders
Neural Information Processing Systems
In this paper, we propose a novel and powerful method to harness Bayesian optimization for V ariational Quantum Eigensolvers (VQEs)--a hybrid quantum-classical protocol used to approximate the ground state of a quantum Hamiltonian.
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PaCo: Parameter-CompositionalMulti-Task ReinforcementLearning
Neural Information Processing Systems
Ontheotherhand,asintelligentagents,humansusuallyspendlesstime learning similar tasks and can acquire new skills using existing ones.
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