quantum circuit
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A Resource scaling for quantum backpropagation methods
Both of the techniques assume bitwise access to the oracle as a classical function.
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On quantum backpropagation, information reuse, and cheating measurement collapse
Computing gradients through backpropagation is crucial to the success of modern deep neural networks.
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Expressive power of tensor-network factorizations for probabilistic modeling
Ivan Glasser, Ryan Sweke, Nicola Pancotti, Jens Eisert, Ignacio Cirac
Whenusedtomodelprobability distributions, theyexhibit tractable likelihoods and admit efficient learning algorithms.
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