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Quantum re-uploading models have been extensively investigated as a form of machine learning within the context of variational quantum algorithms.
“Input Redundancy for Parameterized Quantum Circuits” (2020)
Javier Gil Vidal and Dirk Oliver Theis · 1901
Earlier work this paper cites.
“Variational Fast Forwarding for Quantum Simulation Beyond the Coherence Time”
Cristina Cirstoiu, Zoe Holmes, Joseph Iosue, Lukasz Cincio, Patrick J. Coles, and Andrew Sornborger · 1910
Earlier work this paper cites.
“Probability Inequalities for Sums of Bounded Random Variables”
Wassily Hoeffding · 1963
Earlier work this paper cites.
“Multivariate Beta Distributions and Independence Properties of the Wishart Distribution”
Ingram Olkin and Herman Rubin · 1964
Earlier work this paper cites.
“Approximation by superpositions of a sigmoidal function”
G. Cybenko · 1989
Earlier work this paper cites.
“Approximation capabilities of multilayer feedforward networks”
Kurt Hornik · 1991
Earlier work this paper cites.
“Distributional Identities of Beta and Chi-Squared Variates: A Geometrical Interpretation”
Ralph W. Bailey · 1992
Earlier work this paper cites.
“Elementary gates for quantum computation”
Adriano Barenco, Charles H. Bennett, Richard Cleve, David P. DiVincenzo, Norman Margolus, Peter Shor, Tycho Sleator, John A. Smolin, and Harald Weinfurter · 1995
Earlier work this paper cites.
“Probability and Measure”
Patrick Billingsley · 1995
Earlier work this paper cites.
“The Complexity of the Local Hamiltonian Problem” (2005)
Julia Kempe, Alexei Kitaev, and Oded Regev · 2005
Earlier work this paper cites.
“Low depth mechanisms for quantum optimization”
Jarrod R. McClean, Matthew P. Harrigan, Masoud Mohseni, Nicholas C. Rubin, Zhang Jiang, Sergio Boixo, Vadim N. Smelyanskiy, Ryan Babbush, and Hartmut Neven · 2008
Earlier work this paper cites.
“The effect of data encoding on the expressive power of variational quantum machine learning models”
Maria Schuld, Ryan Sweke, and Johannes Jakob Meyer · 2008
Earlier work this paper cites.
“Quantum field theory in a nutshell”
A. Zee · 2010
Earlier work this paper cites.
“Answer to ”reference for multidimensional gaussian integral”” (2012)
user26872 · 2012
Earlier work this paper cites.
“On the difficulty of training Recurrent Neural Networks” (2013)
Razvan Pascanu, Tomas Mikolov, and Yoshua Bengio · 2013
Earlier work this paper cites.
“A variational eigenvalue solver on a photonic quantum processor”
Alberto Peruzzo, Jarrod McClean, Peter Shadbolt, Man-Hong Yung, Xiao-Qi Zhou, Peter J. Love, Alán Aspuru-Guzik, and Jeremy L. O’Brien · 2014
Earlier work this paper cites.
“A Quantum Approximate Optimization Algorithm” (2014)
Edward Farhi, Jeffrey Goldstone, and Sam Gutmann · 2014
Earlier work this paper cites.
“Exploratory Landscape Analysis of Continuous Space Optimization Problems Using Information Content”
Mario A. Muñoz, Michael Kirley, and Saman K. Halgamuge · 2015
Earlier work this paper cites.
“The theory of variational hybrid quantum-classical algorithms”
Jarrod R. McClean, Jonathan Romero, Ryan Babbush, and Alán Aspuru-Guzik · 2016
Earlier work this paper cites.
“Efficient Variational Quantum Simulator Incorporating Active Error Minimization”
Ying Li and Simon C. Benjamin · 2017
Earlier work this paper cites.
“Unsupervised Machine Learning on a Hybrid Quantum Computer” (2017)
J. S. Otterbach, R. Manenti, N. Alidoust, A. Bestwick, M. Block, B. Bloom, S. Caldwell, N. Didier, E. Schuyler Fried, S. Hong, P. Karalekas, C. B. Osborn, A. Papageorge, E. C. Peterson, G. Prawiroatmodjo, N. Rubin, Colm A. Ryan, D. Scarabelli, M. Scheer, E. A. Sete, P. Sivarajah, Robert S. Smith, A. Staley, N. Tezak, W. J. Zeng, A. Hudson, Blake R. Johnson, M. Reagor, M. P. da Silva, and C. Rigetti · 2017
Earlier work this paper cites.
“On the Expressive Power of Deep Neural Networks” (2017)
Maithra Raghu, Ben Poole, Jon Kleinberg, Surya Ganguli, and Jascha Sohl-Dickstein · 2017
Earlier work this paper cites.
“Spectrally-normalized margin bounds for neural networks” (2017)
Peter Bartlett, Dylan J. Foster, and Matus Telgarsky · 2017
Cited alongside, same era.
“Quantum Computing in the NISQ era and beyond”
John Preskill · 2018
Cited alongside, same era.
Kosuke Mitarai, Makoto Negoro, Masahiro Kitagawa, and Keisuke Fujii · 2018
Cited alongside, same era.
“Quantum generative adversarial networks”
Pierre-Luc Dallaire-Demers and Nathan Killoran · 2018
Cited alongside, same era.
“Barren plateaus in quantum neural network training landscapes”
Jarrod R. McClean, Sergio Boixo, Vadim N. Smelyanskiy, Ryan Babbush, and Hartmut Neven · 2018
Cited alongside, same era.
“One qubit as a universal approximant”
Adrián Pérez-Salinas, David López-Núñez, Artur García-Sáez, P. Forn-Díaz, and José I. Latorre · 2021
Later among the works it cites.
“Evaluation of parameterized quantum circuits: On the relation between classification accuracy, expressibility, and entangling capability”
Thomas Hubregtsen, Josef Pichlmeier, Patrick Stecher, and Koen Bertels · 2021
Later among the works it cites.
“Theory of overparametrization in quantum neural networks” (2021)
Martin Larocca, Nathan Ju, Diego García-Martín, Patrick J. Coles, and M. Cerezo · 2021
Later among the works it cites.
“Encoding-dependent generalization bounds for parametrized quantum circuits”
Matthias C. Caro, Elies Gil-Fuster, Johannes Jakob Meyer, Jens Eisert, and Ryan Sweke · 2021
Later among the works it cites.
“Cost function dependent barren plateaus in shallow parametrized quantum circuits”
M. Cerezo, Akira Sone, Tyler Volkoff, Lukasz Cincio, and Patrick J. Coles · 2021
Later among the works it cites.
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Sergio Boixo, Sergei V. Isakov, Vadim N. Smelyanskiy, Ryan Babbush, Nan Ding, Zhang Jiang, Michael J. Bremner, John M. Martinis, and Hartmut Neven · 2018
Cited alongside, same era.
“Constrained Variational Quantum Eigensolver: Quantum Computer Search Engine in the Fock Space”
Ilya G. Ryabinkin, Scott N. Genin, and Artur F. Izmaylov · 2019
Cited alongside, same era.
“Quantum Chemistry in the Age of Quantum Computing”
Yudong Cao, Jonathan Romero, Jonathan P. Olson, Matthias Degroote, Peter D. Johnson, Mária Kieferová, Ian D. Kivlichan, Tim Menke, Borja Peropadre, Nicolas P. D. Sawaya, Sukin Sim, Libor Veis, and Alán Aspuru-Guzik · 2019
Cited alongside, same era.
“Variational ansatz-based quantum simulation of imaginary time evolution”
Sam McArdle, Tyson Jones, Suguru Endo, Ying Li, Simon C. Benjamin, and Xiao Yuan · 2019
Cited alongside, same era.
“Theory of variational quantum simulation”
Xiao Yuan, Suguru Endo, Qi Zhao, Ying Li, and Simon C. Benjamin · 2019
Cited alongside, same era.
“Supervised learning with quantum-enhanced feature spaces”
Vojtěch Havlíček, Antonio D. Córcoles, Kristan Temme, Aram W. Harrow, Abhinav Kandala, Jerry M. Chow, and Jay M. Gambetta · 2019
Cited alongside, same era.
“Quantum Generative Adversarial Networks for learning and loading random distributions”
Christa Zoufal, Aurélien Lucchi, and Stefan Woerner · 2019
Cited alongside, same era.
“Regularisation of neural networks by enforcing Lipschitz continuity”
Henry Gouk, Eibe Frank, Bernhard Pfahringer, and Michael J. Cree · 2021
Later among the works it cites.
“Noisy intermediate-scale quantum algorithms”
Kishor Bharti, Alba Cervera-Lierta, Thi Ha Kyaw, Tobias Haug, Sumner Alperin-Lea, Abhinav Anand, Matthias Degroote, Hermanni Heimonen, Jakob S. Kottmann, Tim Menke, Wai-Keong Mok, Sukin Sim, Leong-Chuan Kwek, and Alán Aspuru-Guzik · 2022
Later among the works it cites.
“Beyond Barren Plateaus: Quantum Variational Algorithms Are Swamped With Traps” (2022)
Eric R. Anschuetz and Bobak T. Kiani · 2022
Later among the works it cites.
“Connecting Ansatz Expressibility to Gradient Magnitudes and Barren Plateaus”
Zoë Holmes, Kunal Sharma, M. Cerezo, and Patrick J. Coles · 2022
Later among the works it cites.
“Diagnosing Barren Plateaus with Tools from Quantum Optimal Control”
Martin Larocca, Piotr Czarnik, Kunal Sharma, Gopikrishnan Muraleedharan, Patrick J. Coles, and M. Cerezo · 2022
Later among the works it cites.
“Escaping Local Optima with Local Search: A Theory-Driven Discussion”
Tobias Friedrich, Timo Kötzing, Martin S. Krejca, and Amirhossein Rajabi · 2022
Later among the works it cites.
“Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks” (2022)
Louis Schatzki, Martin Larocca, Quynh T. Nguyen, Frederic Sauvage, and M. Cerezo · 2022
Later among the works it cites.
“Generalization despite overfitting in quantum machine learning models” (2022)
Evan Peters and Maria Schuld · 2022
Later among the works it cites.
“Subtleties in the trainability of quantum machine learning models”
Supanut Thanasilp, Samson Wang, Nhat A. Nghiem, Patrick J. Coles, and M. Cerezo · 2023
Closest in time.
“Quantum machine learning beyond kernel methods”
Sofiene Jerbi, Lukas J. Fiderer, Hendrik Poulsen Nautrup, Jonas M. Kübler, Hans J. Briegel, and Vedran Dunjko · 2023
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“Github repository: QRU_average
Alice Barthe and Adrián Pérez-Salinas · 2023
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“Analyzing variational quantum landscapes with information content” (2023)
Adrián Pérez-Salinas, Hao Wang, and Xavier Bonet-Monroig · 2023
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“Classical surrogates for quantum learning models”
Franz J. Schreiber, Jens Eisert, and Johannes Jakob Meyer · 2023
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“Exponential data encoding for quantum supervised learning”
S. Shin, Y. S. Teo, and H. Jeong · 2023
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“Classical simulations of noisy variational quantum circuits” (2023)
Enrico Fontana, Manuel S. Rudolph, Ross Duncan, Ivan Rungger, and Cristina Cîrstoiu · 2023
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“Classical surrogate simulation of quantum systems with LOWESA” (2023)
Manuel S. Rudolph, Enrico Fontana, Zoë Holmes, and Lukasz Cincio · 2023
Closest in time.
“Classical simulation of peaked shallow quantum circuits” (2023)
Sergey Bravyi, David Gosset, and Yinchen Liu · 2023
Closest in time.