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There is currently a large interest in understanding the potential advantages quantum devices can offer for probabilistic modelling.
A theory of the learnable
Leslie G. Valiant · 1984
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Learning integer lattices
David Helmbold, Robert Sloan, and Manfred K. Warmuth · 1992
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On-line learning with malicious noise and the closure algorithm
Peter Auer and Nicoló Cesa-Bianchi · 1994
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On the learnability of discrete distributions
Michael Kearns, Yishay Mansour, Dana Ron, Ronitt Rubinfeld, Robert E. Schapire, and Linda Sellie · 1994
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An introduction to computational learning theory
Michael J. Kearns and Umesh Virkumar Vazirani · 1994
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The Heisenberg representation of quantum computers
Daniel Gottesman · 1998
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Efficient noise-tolerant learning from statistical queries
Michael Kearns · 1998
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Universal quantum gates
Jean-Luc Brylinski and Ranee Brylinski · 2002
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Practical scheme for quantum computation with any two-qubit entangling gate
Michael J. Bremner, Christopher M. Dawson, Jennifer L. Dodd, Alexei Gilchrist, Aram W. Harrow, Duncan Mortimer, Michael A. Nielsen, and Tobias J. Osborne · 2002
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Adaptive quantum computation, constant depth quantum circuits and arthur-merlin games
Barbara M. Terhal and David P DiVincenzo · 2002
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Clifford group, stabilizer states, and linear and quadratic operations over gf(2)
Jeroen Dehaene and Bart De Moor · 2003
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Improved simulation of stabilizer circuits
Scott Aaronson and Daniel Gottesman · 2004
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The learnability of quantum states
Scott Aaronson · 2007
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Classical simulation of commuting quantum computations implies collapse of the polynomial hierarchy
Michael J. Bremner, Richard Jozsa, and Dan J. Shepherd · 2010
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Pseudo-randomness and Learning in Quantum Computation
Richard A. Low · 2010
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A kernel two-sample test
Arthur Gretton, Karsten M Borgwardt, Malte J Rasch, Bernhard Schölkopf, and Alexander Smola · 2012
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Auto-encoding variational bayes
Diederik P. Kingma and Max Welling · 2013
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Learning from satisfying assignments
Anindya De, Ilias Diakonikolas, and Rocco A. Servedio · 2014
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Understanding machine learning: From theory to algorithms
Shai Shalev-Shwartz and Shai Ben-David · 2014
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On learning distributions from their samples
Sudeep Kamath, Alon Orlitsky, Dheeraj Pichapati, and Ananda Theertha Suresh · 2015
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Local random quantum circuits are approximate polynomial-designs
Fernando G. S. L. Brandao, Aram W. Harrow, and Michal Horodecki · 2016
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Learning structured distributions
Ilias Diakonikolas · 2016
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Statistical Query Learning
Vitaly Feldman · 2016
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The Clifford group forms a unitary 3-design
Zak Webb · 2016
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Complexity-theoretic foundations of quantum supremacy experiments
Scott Aaronson and Lijie Chen · 2017
Cited alongside, same era.
Guest column: A survey of quantum learning theory
Srinivasan Arunachalam and Ronald de Wolf · 2017
Cited alongside, same era.
Statistical Query Lower Bounds for Robust Estimation of High-Dimensional Gaussians and Gaussian Mixtures
Ilias Diakonikolas, Daniel M. Kane, and Alistair Stewart · 2017
Cited alongside, same era.
A General Characterization of the Statistical Query Complexity
Vitaly Feldman · 2017
Cited alongside, same era.
Introduction to property testing
Oded Goldreich · 2017
Cited alongside, same era.
Learning in Implicit Generative Models
Shakir Mohamed and Balaji Lakshminarayanan · 2017
Quantum Hamiltonian-Based Models and the Variational Quantum Thermalizer Algorithm
Guillaume Verdon, Jacob Marks, Sasha Nanda, Stefan Leichenauer, and Jack Hidary · 2019
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Variational quantum algorithms
Marco Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C. Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R. McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, and Patrick J. Coles · 2020
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A short note on learning discrete distributions
Clément L. Canonne · 2020
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A survey on distribution testing: Your data is big. But is it blue?
Clément L. Canonne · 2020
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The Born supremacy: Quantum advantage and training of an Ising born machine
Brian Coyle, Daniel Mills, Vincent Danos, and Elham Kashefi · 2020
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Cited alongside, same era.
Learning stabilizer states by Bell sampling
Ashley Montanaro · 2017
Cited alongside, same era.
An automatic inequality prover and instance optimal identity testing
Gregory Valiant and Paul Valiant · 2017
Cited alongside, same era.
Multiqubit Clifford groups are unitary 3-designs
Huangjun Zhu · 2017
Cited alongside, same era.
Quantum generative adversarial networks
Pierre-Luc Dallaire-Demers and Nathan Killoran · 2018
Cited alongside, same era.
A quantum machine learning algorithm based on generative models
Xun Gao, Zhengyu Zhang, and Luming Duan · 2018
Cited alongside, same era.
Aram Harrow and Saeed Mehraban · 2018
Cited alongside, same era.
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Random quantum circuits anti-concentrate in log depth
Alexander M Dalzell, Nicholas Hunter-Jones, and Fernando GSL Brandão · 2020
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Quantum certification and benchmarking
Jens Eisert, Dominik Hangleiter, Nathan Walk, Ingo Roth, Damiam Markham, Rhea Parekh, Ulysse Chabaud, and Elham Kashefi · 2020
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Sampling and the complexity of nature
Dominik Hangleiter · 2020
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Predicting many properties of a quantum system from very few measurements
Hsin-Yuan Huang, Richard Kueng, and John Preskill · 2020
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Normalizing flows: An introduction and review of current methods
Ivan Kobyzev, Simon Prince, and Marcus Brubaker · 2020
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Quantum supremacy and random circuits
Ramis Movassagh · 2020
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Learnability and complexity of quantum samples
Murphy Yuezhen Niu, Andrew M. Dai, Li Li, Augustus Odena, Zhengli Zhao, Vadim Smelyanskyi, Hartmut Neven, and Sergio Boixo · 2020
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Generation of High-Resolution Handwritten Digits with an Ion-Trap Quantum Computer
Manuel S. Rudolph, Ntwali Bashige Toussaint, Amara Katabarwa, Sonika Johri, Borja Peropadre, and Alejandro Perdomo-Ortiz · 2020
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Shtetl-optimized: Yet more mistakes in papers
Scott Aaronson · 2021
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Efficient Learning of Non-Interacting Fermion Distributions
Scott Aaronson and Sabee Grewal · 2021
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Spoofing linear cross-entropy benchmarking in shallow quantum circuits
Boaz Barak, Chi-Ning Chou, and Xun Gao · 2021
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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, Wai-Keong Mok, Sukin Sim, Leong-Chuan Kwek, and Alán Aspuru-Guzik · 2021
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Noise and the frontier of quantum supremacy
Adam Bouland, Bill Fefferman, Zeph Landau, and Yunchao Liu · 2021
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Hadamard-free circuits expose the structure of the clifford group
Sergey Bravyi and Dmitri Maslov · 2021
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On the Hardness of PAC-learning stabilizer States with Noise
Aravind Gollakota and Daniel Liang · 2021
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Improved spectral gaps for random quantum circuits: Large local dimensions and all-to-all interactions
Jonas Haferkamp and Nicholas Hunter-Jones · 2021
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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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CRediT – contributor roles taxonomy
NISO · 2021
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On the quantum versus classical learnability of discrete distributions
Ryan Sweke, Jean-Pierre Seifert, Dominik Hangleiter, and Jens Eisert · 2021
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