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Quantum neural networks represent a new machine learning paradigm that has recently attracted much attention due to its potential promise.
Zur Quantenmechanik der Stoßvorgänge
Max Born · 1926
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Approximation by superpositions of a sigmoidal function
G. Cybenko · 1989
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Multilayer feedforward networks are universal approximators
Kurt Hornik, Maxwell Stinchcombe, and Halbert White · 1989
Earlier work this paper cites.
Neural networks for pattern recognition
Christopher M Bishop et al · 1995
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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
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Neural networks and deep learning
Michael A Nielsen · 2015
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Barren plateaus in quantum neural network training landscapes
Jarrod R McClean, Sergio Boixo, Vadim N Smelyanskiy, Ryan Babbush, and Hartmut Neven · 2018
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Supervised learning with quantum computers
Maria Schuld and Francesco Petruccione · 2018
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Parameterized quantum circuits as machine learning models
Marcello Benedetti, Erika Lloyd, Stefan Sack, and Mattia Fiorentini · 2019
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Fourier neural operator for parametric partial differential equations
Zongyi Li, Nikola Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Kaushik Bhattacharya, Andrew Stuart, and Anima Anandkumar · 2020
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A rigorous and robust quantum speed-up in supervised machine learning
Yunchao Liu, Srinivasan Arunachalam, and Kristan Temme · 2021
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Generalization in quantum machine learning from few training data
Matthias C. Caro, Hsin-Yuan Huang, M. Cerezo, Kunal Sharma, Andrew Sornborger, Lukasz Cincio, and Patrick J. Coles · 2021
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Power of data in quantum machine learning
Hsin-Yuan Huang, Michael Broughton, Masoud Mohseni, Ryan Babbush, Sergio Boixo, Hartmut Neven, and Jarrod R McClean · 2021
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Noise-induced barren plateaus in variational quantum algorithms
Samson Wang, Enrico Fontana, Marco Cerezo, Kunal Sharma, Akira Sone, Lukasz Cincio, and Patrick J Coles · 2021
Classical-to-quantum transfer learning for spoken command recognition based on quantum neural networks
Jun Qi and Javier Tejedor · 2022
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Generalization despite overfitting in quantum machine learning models
Evan Peters and Maria Schuld · 2022
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Quantum machine learning: from physics to software engineering
Alexey Melnikov, Mohammad Kordzanganeh, Alexander Alodjants, and Ray-Kuang Lee · 2023
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Benchmarking simulated and physical quantum processing units using quantum and hybrid algorithms
Mohammad Kordzanganeh, Markus Buchberger, Basil Kyriacou, Maxim Povolotskii, Wilhelm Fischer, Andrii Kurkin, Wilfrid Somogyi, Asel Sagingalieva, Markus Pflitsch, and Alexey Melnikov · 2023
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Hybrid quantum ResNet for car classification and its hyperparameter optimization
Asel Sagingalieva, Andrii Kurkin, Artem Melnikov, Daniil Kuhmistrov, et al · 2023
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Effect of data encoding on the expressive power of variational quantum-machine-learning models
Maria Schuld, Ryan Sweke, and Johannes Jakob Meyer · 2021
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Challenges and opportunities in quantum machine learning
M. Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, and Patrick J. Coles · 2022
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Practical application-specific advantage through hybrid quantum computing
Michael Perelshtein, Asel Sagingalieva, Karan Pinto, Vishal Shete, Alexey Pakhomchik, Artem Melnikov, Florian Neukart, Georg Gesek, Alexey Melnikov, and Valerii Vinokur · 2022
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When bert meets quantum temporal convolution learning for text classification in heterogeneous computing
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Hybrid quantum neural network for drug response prediction
Asel Sagingalieva, Mohammad Kordzanganeh, Nurbolat Kenbayev, Daria Kosichkina, Tatiana Tomashuk, and Alexey Melnikov · 2023
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Quantum algorithms applied to satellite mission planning for Earth observation
Serge Rainjonneau, Igor Tokarev, Sergei Iudin, Saaketh Rayaprolu, Karan Pinto, Daria Lemtiuzhnikova, Miras Koblan, Egor Barashov, Mo Kordzanganeh, Markus Pflitsch, and Alexey Melnikov · 2023
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Theoretical error performance analysis for variational quantum circuit based functional regression
Jun Qi, Chao-Han Huck Yang, Pin-Yu Chen, and Min-Hsiu Hsieh · 2023
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