Fetching the paper…
Reading the bibliography…
The superiority of variational quantum algorithms (VQAs) such as quantum neural networks (QNNs) and variational quantum eigen-solvers (VQEs) heavily depends on the expressivity of the employed ansatze.
The sizes of compact subsets of hilbert space and continuity of gaussian processes
Richard M Dudley · 1967
Earlier work this paper cites.
Occam’s razor
Anselm Blumer, Andrzej Ehrenfeucht, David Haussler, and Manfred K Warmuth · 1987
Earlier work this paper cites.
A note on a general definition of the coefficient of determination
Nico JD Nagelkerke et al · 1991
Earlier work this paper cites.
Fermionic quantum computation
Sergey B Bravyi and Alexei Yu Kitaev · 2002
Earlier work this paper cites.
On the complexity of linear prediction: Risk bounds, margin bounds, and regularization
Sham M. Kakade, K. Sridharan, and Ambuj Tewari · 2008
Earlier work this paper cites.
Random quantum circuits are approximate 2-designs
Aram W Harrow and Richard A Low · 2009
Earlier work this paper cites.
How often is a random quantum state k-entangled?
Stanisław J Szarek, Elisabeth Werner, and Karol Życzkowski · 2010
Earlier work this paper cites.
Quantum computation and quantum information
Michael A Nielsen and Isaac L Chuang · 2010
Earlier work this paper cites.
Quantum simulation of time-dependent hamiltonians and the convenient illusion of hilbert space
David Poulin, Angie Qarry, Rolando Somma, and Frank Verstraete · 2011
Earlier work this paper cites.
Foundations of machine learning, 2012
Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar · 2012
Earlier work this paper cites.
The nature of statistical learning theory
Vladimir Vapnik · 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.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
Quantum machine learning
Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd · 2017
Earlier work this paper cites.
Quantum computational supremacy
Aram W Harrow and Ashley Montanaro · 2017
Earlier work this paper cites.
Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets
Abhinav Kandala, Antonio Mezzacapo, Kristan Temme, Maika Takita, Markus Brink, Jerry M Chow, and Jay M Gambetta · 2017
Earlier work this paper cites.
Generalization in deep learning
Kenji Kawaguchi, Leslie Pack Kaelbling, and Yoshua Bengio · 2017
Earlier work this paper cites.
Spectrally-normalized margin bounds for neural networks
Peter Bartlett, Dylan Foster, and Matus Telgarsky · 2017
Earlier work this paper cites.
Machine learning & artificial intelligence in the quantum domain: a review of recent progress
Vedran Dunjko and Hans J Briegel · 2018
Earlier work this paper cites.
Quantum computing in the nisq era and beyond
John Preskill · 2018
Earlier work this paper cites.
Quantum circuit learning
Kosuke Mitarai, Makoto Negoro, Masahiro Kitagawa, and Keisuke Fujii · 2018
Earlier work this paper cites.
Barren plateaus in quantum neural network training landscapes
Jarrod R McClean, Sergio Boixo, Vadim N Smelyanskiy, Ryan Babbush, and Hartmut Neven · 2018
Earlier work this paper cites.
Foundations of machine learning
Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar · 2018
Earlier work this paper cites.
Fundamental limitations for measurements in quantum many-body systems
Thomas Barthel and Jianfeng Lu · 2018
Earlier work this paper cites.
Strategies for quantum computing molecular energies using the unitary coupled cluster ansatz
Jonathan Romero, Ryan Babbush, Jarrod R McClean, Cornelius Hempel, Peter J Love, and Alán Aspuru-Guzik · 2018
Earlier work this paper cites.
A survey on deep learning: Algorithms, techniques, and applications
Samira Pouyanfar, Saad Sadiq, Yilin Yan, Haiman Tian, Yudong Tao, Maria Presa Reyes, Mei-Ling Shyu, Shu-Ching Chen, and Sundaraja S Iyengar · 2018
Earlier work this paper cites.
Parameterized quantum circuits as machine learning models
Marcello Benedetti, Erika Lloyd, Stefan Sack, and Mattia Fiorentini · 2019
Earlier work this paper cites.
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.
Training of quantum circuits on a hybrid quantum computer
Daiwei Zhu, Norbert M Linke, Marcello Benedetti, Kevin A Landsman, Nhung H Nguyen, C Huerta Alderete, Alejandro Perdomo-Ortiz, Nathan Korda, A Garfoot, Charles Brecque, et al · 2019
Cited alongside, same era.
Expressibility and entangling capability of parameterized quantum circuits for hybrid quantum-classical algorithms
Sukin Sim, Peter D Johnson, and Alán Aspuru-Guzik · 2019
Cited alongside, same era.
Towards quantum machine learning with tensor networks
William Huggins, Piyush Patil, Bradley Mitchell, K Birgitta Whaley, and E Miles Stoudenmire · 2019
Cited alongside, same era.
Evaluating analytic gradients on quantum hardware
Maria Schuld, Ville Bergholm, Christian Gogolin, Josh Izaac, and Nathan Killoran · 2019
Cited alongside, same era.
Decoding quantum errors with subspace expansions
Jarrod R McClean, Zhang Jiang, Nicholas C Rubin, Ryan Babbush, and Hartmut Neven · 2020
Later among the works it cites.
Learning-based quantum error mitigation
Armands Strikis, Dayue Qin, Yanzhu Chen, Simon C Benjamin, and Ying Li · 2020
Later among the works it cites.
Robust data encodings for quantum classifiers
Ryan LaRose and Brian Coyle · 2020
Later among the works it cites.
Entanglement induced barren plateaus
Carlos Ortiz Marrero, Mária Kieferová, and Nathan Wiebe · 2020
Later among the works it cites.
Stochastic gradient descent for hybrid quantum-classical optimization
Ryan Sweke, Frederik Wilde, Johannes Meyer, Maria Schuld, Paul K Fährmann, Barthélémy Meynard-Piganeau, and Jens Eisert · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Error-mitigated digital quantum simulation
Sam McArdle, Xiao Yuan, and Simon Benjamin · 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 PD Sawaya, et al · 2019
Cited alongside, same era.
An adaptive variational algorithm for exact molecular simulations on a quantum computer
Harper R Grimsley, Sophia E Economou, Edwin Barnes, and Nicholas J Mayhall · 2019
Cited alongside, same era.
Optimization for deep learning: theory and algorithms
Ruoyu Sun · 2019
Cited alongside, same era.
Variational quantum algorithms
M Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, et al · 2020
Cited alongside, same era.
Expressive power of parametrized quantum circuits
Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, and Dacheng Tao · 2020
Cited alongside, same era.
On the learnability of quantum neural networks
Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Shan You, and Dacheng Tao · 2020
Cited alongside, same era.
Quantum computational chemistry
Sam McArdle, Suguru Endo, Alan Aspuru-Guzik, Simon C Benjamin, and Xiao Yuan · 2020
Later among the works it cites.
Openfermion: the electronic structure package for quantum computers
Jarrod R McClean, Nicholas C Rubin, Kevin J Sung, Ian D Kivlichan, Xavier Bonet-Monroig, Yudong Cao, Chengyu Dai, E Schuyler Fried, Craig Gidney, Brendan Gimby, et al · 2020
Later among the works it cites.
Noisy intermediate-scale quantum (nisq) 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, et al · 2021
Closest in time.
Hybrid quantum-classical algorithms and quantum error mitigation
Suguru Endo, Zhenyu Cai, Simon C Benjamin, and Xiao Yuan · 2021
Closest in time.
A grover-search based quantum learning scheme for classification
Yuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, and Dacheng Tao · 2021
Closest in time.
Information-theoretic bounds on quantum advantage in machine learning
Hsin-Yuan Huang, Richard Kueng, and John Preskill · 2021
Closest in time.
Expressivity of quantum neural networks
Yadong Wu, Juan Yao, Pengfei Zhang, and Hui Zhai · 2021
Closest in time.
Generalization in quantum machine learning: a quantum information perspective
Leonardo Banchi, Jason Pereira, and Stefano Pirandola · 2021
Closest in time.
On the statistical complexity of quantum circuits
Kaifeng Bu, Dax Enshan Koh, Lu Li, Qingxian Luo, and Yaobo Zhang · 2021
Closest in time.
Dimensional expressivity analysis of parametric quantum circuits
Lena Funcke, Tobias Hartung, Karl Jansen, Stefan Kühn, and Paolo Stornati · 2021
Closest in time.
Connecting ansatz expressibility to gradient magnitudes and barren plateaus
Zoë Holmes, Kunal Sharma, M Cerezo, and Patrick J Coles · 2021
Closest in time.
Expressibility of the alternating layered ansatz for quantum computation
Kouhei Nakaji and Naoki Yamamoto · 2021
Closest in time.
Mitigating realistic noise in practical noisy intermediate-scale quantum devices
Jinzhao Sun, Xiao Yuan, Takahiro Tsunoda, Vlatko Vedral, Simon C Benjamin, and Suguru Endo · 2021
Closest in time.
Theory of overparametrization in quantum neural networks, 2021
Martin Larocca, Nathan Ju, Diego García-Martín, Patrick J. Coles, and M. Cerezo · 2021
Closest in time.
Spectral bias and task-model alignment explain generalization in kernel regression and infinitely wide neural networks
Abdulkadir Canatar, Blake Bordelon, and Cengiz Pehlevan · 2021
Closest in time.
Encoding-dependent generalization bounds for parametrized quantum circuits
Matthias C Caro, Elies Gil-Fuster, Johannes Jakob Meyer, Jens Eisert, and Ryan Sweke · 2021
Closest in time.
Structural risk minimization for quantum linear classifiers
Casper Gyurik, Dyon van Vreumingen, and Vedran Dunjko · 2021
Closest in time.
A semi-agnostic ansatz with variable structure for quantum machine learning
M Bilkis, M Cerezo, Guillaume Verdon, Patrick J Coles, and Lukasz Cincio · 2021
Closest in time.
Quantum architecture search via deep reinforcement learning
En-Jui Kuo, Yao-Lung L Fang, and Samuel Yen-Chi Chen · 2021
Closest in time.
Structure optimization for parameterized quantum circuits
Mateusz Ostaszewski, Edward Grant, and Marcello Benedetti · 2021
Closest in time.
qubit-adapt-vqe: An adaptive algorithm for constructing hardware-efficient ansätze on a quantum processor
Ho Lun Tang, VO Shkolnikov, George S Barron, Harper R Grimsley, Nicholas J Mayhall, Edwin Barnes, and Sophia E Economou · 2021
Closest in time.
Neural predictor based quantum architecture search
Shi-Xin Zhang, Chang-Yu Hsieh, Shengyu Zhang, and Hong Yao · 2021
Closest in time.