Quantum Computing in Machine Learning
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-8004-6_7
Reference27 articles.
1. Nielsen MA, Chuang IL (2010) Quantum computation and quantum information. Cambridge University Press, New York, Hardback. ISBN 978-1-107-00217-3
2. Sleeman J, Dorband J, Halem M (2020) A hybrid quantum enabled RBM advantage: convolutional autoencoders for quantum image compression and generative learning. In: Quantum information science, sensing, and computation XII, vol 11391. International Society for Optics and Photonics, p 113910B
3. Xu P, He Z, Qiu T, Ma H (2020) Quantum image processing algorithm using edge extraction based on Kirsch operator. Opt Express 28(9):12508–12517
4. Yan F, Chen K, Iliyasu AM, Hirota K (2020) Circuit-based modular implementation of quantum ghost imaging. IEEE Access 8:23054–23068
5. Henderson M, Shakya S, Pradhan S, Cook T (2020) Quanvolutional neural networks: powering image recognition with quantum circuits. Quant Mach Intell 2(1):1–9
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