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quant-ph2022★ 2 cited
Provably efficient variational generative modeling of quantum many-body systems via quantum-probabilistic information geometry
Faris M. Sbahi, Antonio J. Martinez, Sahil Patel +4
The dual tasks of quantum Hamiltonian learning and quantum Gibbs sampling are relevant to many important problems in physics and chemistry. In the low temperature regime, algorithm…
quant-ph2022★ 162 cited
Group-Invariant Quantum Machine Learning
Martin Larocca, Frederic Sauvage, Faris M. Sbahi +3
Quantum Machine Learning (QML) models are aimed at learning from data encoded in quantum states. Recently, it has been shown that models with little to no inductive biases (i.e., w…