# Absence of Barren Plateaus in Quantum Convolutional Neural Networks

@article{Pesah2021AbsenceOB, title={Absence of Barren Plateaus in Quantum Convolutional Neural Networks}, author={Arthur Pesah and M Cerezo and Samson Wang and Tyler Volkoff and Andrew T. Sornborger and Patrick J. Coles}, journal={ArXiv}, year={2021}, volume={abs/2011.02966} }

Quantum neural networks (QNNs) have generated excitement around the possibility of efficiently analyzing quantum data. But this excitement has been tempered by the existence of exponentially vanishing gradients, known as barren plateau landscapes, for many QNN architectures. Recently, Quantum Convolutional Neural Networks (QCNNs) have been proposed, involving a sequence of convolutional and pooling layers that reduce the number of qubits while preserving information about relevant data features… Expand

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