A classical network trained to output PQC initial parameters across Hamiltonian tasks gives faster VQE convergence in small simulations, but the approach is an extension of Meta-VQE rather than a true MAML implementation.
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Q-MAML: Quantum Model-Agnostic Meta-Learning for Variational Quantum Algorithms
A classical network trained to output PQC initial parameters across Hamiltonian tasks gives faster VQE convergence in small simulations, but the approach is an extension of Meta-VQE rather than a true MAML implementation.