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In recent years, quantum computing (QC) has been getting a lot of attention from industry and academia.
P. W. Shor, “Scheme for reducing decoherence in quantum computer memory,” Physical Review A , vol. 52, no. 4, p. R2493, 1995
1995
Earlier work this paper cites.
N. Wiebe, A. Kapoor, and K. M. Svore, “Quantum deep learning,” CoRR , vol. abs/1412.3489, 2014
2014
Earlier work this paper cites.
G. Carleo, I. Cirac, K. Cranmer, L. Daudet, M. Schuld, N. Tishby, L. Vogt-Maranto, and L. Zdeborová, “Machine learning and the physical sciences,” Reviews of Modern Physics , vol. 91, no. 4, p. 045002, 2019
2019
Earlier work this paper cites.
S. Oh, J. Choi, and J. Kim, “A tutorial on quantum convolutional neural networks (QCNN),” in Proc. of IEEE Int’l Conf. on ICT Convergence (ICTC) , October 2020
2020
Earlier work this paper cites.
S. Y.-C. Chen, C.-H. H. Yang, J. Qi, P.-Y. Chen, X. Ma, and H.-S. Goan, “Variational quantum circuits for deep reinforcement learning,” IEEE Access , vol. 8, pp. 141 007–141 024, 2020
2020
Cited alongside, same era.
J. Park, S. Samarakoon, A. Elgabli, J. Kim, M. Bennis, S.-L. Kim, and M. Debbah, “Communication-efficient and distributed learning over wireless networks: Principles and applications,” Proceedings of the IEEE , vol. 109, no. 5, pp. 796–819, 2021
2021
Cited alongside, same era.
Z. Hong, J. Wang, X. Qu, X. Zhu, J. Liu, and J. Xiao, “Quantum convolutional neural network on protein distance prediction,” in Proc. IEEE Int’l Joint Conf. on Neural Networks (IJCNN) , July 2021
2021
Cited alongside, same era.
Y. Kwak, W. J. Yun, S. Jung, and J. Kim, “Quantum neural networks: Concepts, applications, and challenges,” in Proc. IEEE Int’l Conf. on Ubiquitous and Future Networks (ICUFN) , August 2021
2021
Cited alongside, same era.
Y. Kwak, W. J. Yun, S. Jung, J.-K. Kim, and J. Kim, “Introduction to quantum reinforcement learning: Theory and PennyLane-based implementation,” in PRoc. IEEE Int’l Conf. on ICT Convergence (ICTC) , October 2021
2021
Later among the works it cites.
J. Biamonte, “Universal variational quantum computation,” Physical Review A , vol. 103, no. 3, p. L030401, 2021
2021
Later among the works it cites.
M. Schuld and N. Killoran, “Is quantum advantage the right goal for quantum machine learning?” CoRR , vol. abs:2203.01340, 2022
2022
Closest in time.
H. Wang, Y. Ding, J. Gu, Z. Li, Y. Lin, D. Z. Pan, F. T. Chong, and S. Han, “QuantumNAS: Noise-adaptive search for robust quantum circuits,” in Proc. IEEE Int’l Symposium on High-Performance Computer Architecture (HPCA) , April 2022
2022
Closest in time.
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