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Learning-to-learn for QNNs: learning few-shot optimization of quantum neural networks with classical neural networks

Learning-to-learn for QNNs

Learning few-shot optimization of quantum neural networks with classical neural networks, on real quantum hardware. Implemented using PennyLane & PyTorch on QPU-backends of Rigetti & IBM Q.

Inspired by https://arxiv.org/abs/1907.05415.

Hackathon project for Quantum Stream at Creative Destruction Lab (July 2019) by Clément Javerzac-Galy, Seyed Arash Sheikholeslam, Saamaan Pourtavakoli and Karel Dumon.