Fetching the paper…
Reading the bibliography…
Variational quantum algorithms (VQAs) are the quantum analog of classical neural networks (NNs).
An efficient method for finding the minimum of a function of several variables without calculating derivatives
Powell, M. J. D. 1964 · 1964
Earlier work this paper cites.
Multivariate stochastic approximation using a simultaneous perturbation gradient approximation
Spall, J. 1992 · 1992
Earlier work this paper cites.
Autoencoders, Minimum Description Length and Helmholtz Free Energy
Hinton, G. E.; and Zemel, R. S. 1993 · 1993
Earlier work this paper cites.
Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets
Kandala, A.; Mezzacapo, A.; Temme, K.; Takita, M.; Brink, M.; Chow, J. M.; and Gambetta, J. M. 2017 · 2017
Earlier work this paper cites.
Quantum autoencoders for efficient compression of quantum data
Romero, J.; Olson, J. P.; and Aspuru-Guzik, A. 2017 · 2017
Earlier work this paper cites.
Quantum generalisation of feedforward neural networks
Wan, K. H.; Dahlsten, O.; Kristjánsson, H.; Gardner, R.; and Kim, M. S. 2017 · 2017
Earlier work this paper cites.
Shadow Tomography of Quantum States
Aaronson, S. 2018 · 2018
Earlier work this paper cites.
Quantum-inspired low-rank stochastic regression with logarithmic dependence on the dimension
Gilyén, A.; Lloyd, S.; and Tang, E. 2018 · 2018
Earlier work this paper cites.
Quantum autoencoders via quantum adders with genetic algorithms
Lamata, L.; Alvarez-Rodriguez, U.; Martín-Guerrero, J. D.; Sanz, M.; and Solano, E. 2018 · 2018
Earlier work this paper cites.
Barren plateaus in quantum neural network training landscapes
McClean, J. R.; Boixo, S.; Smelyanskiy, V. N.; Babbush, R.; and Neven, H. 2018 · 2018
Earlier work this paper cites.
Quantum circuit learning
Mitarai, K.; Negoro, M.; Kitagawa, M.; and Fujii, K. 2018 · 2018
Cited alongside, same era.
A Universal Training Algorithm for Quantum Deep Learning
Verdon, G.; Pye, J.; and Broughton, M. 2018 · 2018
Cited alongside, same era.
Quantum convolutional neural networks
Cong, I.; Choi, S.; and Lukin, M. D. 2019 · 2019
Cited alongside, same era.
From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz
Hadfield, S.; Wang, Z.; O'Gorman, B.; Rieffel, E.; Venturelli, D.; and Biswas, R. 2019 · 2019
Cited alongside, same era.
Experimental Realization of a Quantum Autoencoder: The Compression of Qutrits via Machine Learning
Pepper, A.; Tischler, N.; and Pryde, G. J. 2019 · 2019
Cited alongside, same era.
A Quantum-Inspired Classical Algorithm for Recommendation Systems
Learnability of the output distributions of local quantum circuits
Hinsche, M.; Ioannou, M.; Nietner, A.; Haferkamp, J.; Quek, Y.; Hangleiter, D.; Seifert, J.-P.; Eisert, J.; and Sweke, R. 2021 · 2021
Later among the works it cites.
VSQL: Variational Shadow Quantum Learning for Classification
Li, G.; Song, Z.; and Wang, X. 2021 · 2021
Later among the works it cites.
Expressibility of the alternating layered ansatz for quantum computation
Nakaji, K.; and Yamamoto, N. 2021 · 2021
Later among the works it cites.
Absence of Barren Plateaus in Quantum Convolutional Neural Networks
Pesah, A.; Cerezo, M.; Wang, S.; Volkoff, T.; Sornborger, A. T.; and Coles, P. J. 2021 · 2021
Later among the works it cites.
Quantum Principal Component Analysis Only Achieves an Exponential Speedup Because of Its State Preparation Assumptions
Tang, E. 2021 · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Tang, E. 2019 · 2019
Cited alongside, same era.
Predicting many properties of a quantum system from very few measurements
Huang, H.-Y.; Kueng, R.; and Preskill, J. 2020 · 2020
Cited alongside, same era.
Effect of barren plateaus on gradient-free optimization
Arrasmith, A.; Cerezo, M.; Czarnik, P.; Cincio, L.; and Coles, P. J. 2021 · 2021
Cited alongside, same era.
IBM Quantum breaks the 100-qubit processor barrier
Chow, J.; Dial, O.; and Gambetta, J. 2021 · 2021
Cited alongside, same era.
Variational quantum algorithms
Cerezo, M.; Arrasmith, A.; Babbush, R.; Benjamin, S. C.; Endo, S.; Fujii, K.; McClean, J. R.; Mitarai, K.; Yuan, X.; Cincio, L.; and Coles, P. J. 2021a
Cited in the paper.
Cost function dependent barren plateaus in shallow parametrized quantum circuits
Cerezo, M.; Sone, A.; Volkoff, T.; Cincio, L.; and Coles, P. J. 2021b
Cited in the paper.
Power of data in quantum machine learning
Huang, H.-Y.; Broughton, M.; Mohseni, M.; Babbush, R.; Boixo, S.; Neven, H.; and McClean, J. R. 2021a
Cited in the paper.
Wu, A.; Li, G.; Wang, Y.; Feng, B.; Ding, Y.; and Xie, Y. 2021 · 2021
Later among the works it cites.
An improved quantum-inspired algorithm for linear regression
Gilyén, A.; Song, Z.; and Tang, E. 2022 · 2022
Closest in time.
Avoiding Barren Plateaus Using Classical Shadows
Sack, S. H.; Medina, R. A.; Michailidis, A. A.; Kueng, R.; and Serbyn, M. 2022 · 2022
Closest in time.
Unitary block optimization for variational quantum algorithms
Slattery, L.; Villalonga, B.; and Clark, B. K. 2022 · 2022
Closest in time.