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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-ph2020
TensorFlow Quantum: A Software Framework for Quantum Machine Learning
Michael Broughton, Guillaume Verdon, Trevor McCourt +26
We introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data. This framework offers high…