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The neural network and quantum computing are both significant and appealing fields, with their interactive disciplines promising for large-scale computing tasks that are untackled by conventional computers.
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Shmuel Winograd · 1978
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An improved quantum fourier transform algorithm and applications
Lisa Hales and Sean Hallgren · 2000
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MA Reed, J Chen, AM Rawlett, DW Price, and JM Tour · 2001
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Michael A Nielsen and Isaac Chuang · 2002
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Quantum convolution and quantum correlation algorithms are physically impossible
Chris Lomont · 2003
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Quantum random access memory
Vittorio Giovannetti, Seth Lloyd, and Lorenzo Maccone · 2008
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Quantum algorithms for supervised and unsupervised machine learning
Seth Lloyd, Masoud Mohseni, and Patrick Rebentrost · 2013
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Quantum algorithms for nearest-neighbor methods for supervised and unsupervised learning
Nathan Wiebe, Ashish Kapoor, and Krysta Svore · 2014
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Quantum principal component analysis
Seth Lloyd, Masoud Mohseni, and Patrick Rebentrost · 2014
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Quantum support vector machine for big data classification
Patrick Rebentrost, Masoud Mohseni, and Seth Lloyd · 2014
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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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A quantum approximate optimization algorithm
Edward Farhi, Jeffrey Goldstone, and Sam Gutmann · 2014
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Spectral representations for convolutional neural networks
Oren Rippel, Jasper Snoek, and Ryan P Adams · 2015
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On the robustness of bucket brigade quantum ram
Srinivasan Arunachalam, Vlad Gheorghiu, Tomas Jochym-O’Connor, Michele Mosca, and Priyaa Varshinee Srinivasan · 2015
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You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Quantum recommendation systems
Iordanis Kerenidis and Anupam Prakash · 2016
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The theory of variational hybrid quantum-classical algorithms
Jarrod R McClean, Jonathan Romero, Ryan Babbush, and Alán Aspuru-Guzik · 2016
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Quantum machine learning
Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd · 2017
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Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q Weinberger · 2017
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Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling · 2017
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Fcnn: Fourier convolutional neural networks
Harry Pratt, Bryan Williams, Frans Coenen, and Yalin Zheng · 2017
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Diffusion convolutional recurrent neural network: Data-driven traffic forecasting
Yaguang Li, Rose Yu, Cyrus Shahabi, and Yan Liu · 2017
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Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting
A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Windowed fourier transform and general wavelet algorithms in quantum computation
Guangsheng Ma, Hongbo Li, and Jiman Zhao · 2019
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Quantum algorithms for deep convolutional neural networks
Iordanis Kerenidis, Jonas Landman, and Anupam Prakash · 2019
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Quantum convolutional neural networks
Iris Cong, Soonwon Choi, and Mikhail D Lukin · 2019
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Qdnn: Dnn with quantum neural network layers
Chen Zhao and Xiao-Shan Gao · 2019
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Predicting quantum advantage by quantum walk with convolutional neural networks
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Bing Yu, Haoteng Yin, and Zhanxing Zhu · 2017
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Machine learning & artificial intelligence in the quantum domain: a review of recent progress
Vedran Dunjko and Hans J Briegel · 2018
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A case for variability-aware policies for nisq-era quantum computers
Swamit S Tannu and Moinuddin K Qureshi · 2018
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Quantum computing in the nisq era and beyond
John Preskill · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Image to image translation for domain adaptation
Zak Murez, Soheil Kolouri, David Kriegman, Ravi Ramamoorthi, and Kyungnam Kim · 2018
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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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Alexey A Melnikov, Leonid E Fedichkin, and Alexander Alodjants · 2019
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Circuit-based quantum random access memory for classical data
Daniel K Park, Francesco Petruccione, and June-Koo Kevin Rhee · 2019
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From the quantum approximate optimization algorithm to a quantum alternating operator ansatz
Stuart Hadfield, Zhihui Wang, Bryan O’Gorman, Eleanor G Rieffel, Davide Venturelli, and Rupak Biswas · 2019
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Attention based spatial-temporal graph convolutional networks for traffic flow forecasting
Shengnan Guo, Youfang Lin, Ning Feng, Chao Song, and Huaiyu Wan · 2019
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Guillaume Verdon, Trevor McCourt, Enxhell Luzhnica, Vikash Singh, Stefan Leichenauer, and Jack Hidary · 2019
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Quantum gradient descent for linear systems and least squares
Iordanis Kerenidis and Anupam Prakash · 2020
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Yolov4: Optimal speed and accuracy of object detection
Alexey Bochkovskiy, Chien-Yao Wang, and Hong-Yuan Mark Liao · 2020
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Recurrent neural network wave functions
Mohamed Hibat-Allah, Martin Ganahl, Lauren E Hayward, Roger G Melko, and Juan Carrasquilla · 2020
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Circuit implementation of bucket brigade qram for quantum state preparation
Pablo Antonio Moreno Casares · 2020
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Layerwise learning for quantum neural networks
Andrea Skolik, Jarrod R McClean, Masoud Mohseni, Patrick van der Smagt, and Martin Leib · 2020
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Acceleration of convolutional neural network using fft-based split convolutions
Kamran Chitsaz, Mohsen Hajabdollahi, Nader Karimi, Shadrokh Samavi, and Shahram Shirani · 2020
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Falcon: A fourier transform based approach for fast and secure convolutional neural network predictions
Shaohua Li, Kaiping Xue, Bin Zhu, Chenkai Ding, Xindi Gao, David Wei, and Tao Wan · 2020
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Where to go next: A spatio-temporal gated network for next poi recommendation
Pengpeng Zhao, Anjing Luo, Yanchi Liu, Fuzhen Zhuang, Jiajie Xu, Zhixu Li, Victor S Sheng, and Xiaofang Zhou · 2020
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Stacked spatio-temporal graph convolutional networks for action segmentation
Pallabi Ghosh, Yi Yao, Larry Davis, and Ajay Divakaran · 2020
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A comprehensive survey on graph neural networks
Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and S Yu Philip · 2020
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