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Found 4 papers, 2 papers with code
An invitation to the sample complexity of quantum hypothesis testing
By making use of the wealth of knowledge that already exists in the literature on QHT, we characterize the sample complexity of binary QHT in the symmetric and asymmetric settings, and we provide bounds on the sample complexity of multiple QHT.
Learning Quantum Processes with Memory -- Quantum Recurrent Neural Networks
Recurrent neural networks play an important role in both research and industry.
The $α\to 1$ Limit of the Sharp Quantum Rényi Divergence
Fawzi and Fawzi recently defined the sharp R\'enyi divergence, $D_\alpha^\#$, for $\alpha \in (1, \infty)$, as an additional quantum R\'enyi divergence with nice mathematical properties and applications in quantum channel discrimination and quantum communication.
Quantum Physics Mathematical Physics Mathematical Physics
Efficient Learning for Deep Quantum Neural Networks
Neural networks enjoy widespread success in both research and industry and, with the imminent advent of quantum technology, it is now a crucial challenge to design quantum neural networks for fully quantum learning tasks.
