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Quantum computers have the opportunity to be transformative for a variety of computational tasks.
Quantum mechanical pure states with gaussian wave functions
Schumaker, B. L · 1986
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Squeezed light
Loudon, R. & Knight, P. L · 1987
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Four-mode squeezing
Schumaker, B., Perlmutter, S., Shelby, R. & Levenson, M · 1987
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Reinforcement learning: A survey
Kaelbling, L. P., Littman, M. L. & Moore, A. W · 1996
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Monte carlo implementation of gaussian process models for bayesian regression and classification (1997)
Neal, R. M · 1997
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The spatial behavior of nonclassical light
Kolobov, M. I · 1999
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Holomorphic Methods in Mathematical Physics
Hall, B. C · 1999
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Bayesian calibration of computer models
Kennedy, M. C. & O’Hagan, A · 2001
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Polarization squeezing and continuous-variable polarization entanglement
Korolkova, N., Leuchs, G., Loudon, R., Ralph, T. C. & Silberhorn, C · 2002
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Efficient classical simulation of continuous variable quantum information processes
Bartlett, S. D., Sanders, B. C., Braunstein, S. L. & Nemoto, K · 2002
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Gaussian processes in reinforcement learning
Rasmussen, C. E. & Kuss, M · 2004
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Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning) (The MIT Press, 2005)
Rasmussen, C. E. & Williams, C. K. I · 2005
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Efficient quantum algorithms for simulating sparse hamiltonians
Berry, D. W., Ahokas, G., Cleve, R. & Sanders, B. C · 2007
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A bayesian calibration approach to the thermal problem
Higdon, D., Nakhleh, C., Gattiker, J. & Williams, B · 2008
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Generation of fock states in a superconducting quantum circuit
Hofheinz, M. et al · 2008
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Experimental generation of four-mode continuous-variable cluster states
Yukawa, M., Ukai, R., Van Loock, P. & Furusawa, A · 2008
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Gp-bayesfilters: Bayesian filtering using gaussian process prediction and observation models
Ko, J. & Fox, D · 2009
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Quantum algorithm for linear systems of equations
Harrow, A. W., Hassidim, A. & Lloyd, S · 2009
Cited alongside, same era.
Scikit-learn: Machine learning in Python
Pedregosa, F. et al · 2011
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Observation of two-mode squeezing in the microwave frequency domain
Eichler, C. et al · 2011
Cited alongside, same era.
Qutip 2: A python framework for the dynamics of open quantum systems
Johansson, J. R., Nation, P. D. & Nori, F · 2013
Cited alongside, same era.
A variational eigenvalue solver on a photonic quantum processor
Peruzzo, A. et al · 2014
Cited alongside, same era.
Distillation of the two-mode squeezed state
Kurochkin, Y., Prasad, A. S. & Lvovsky, A · 2014
Cited alongside, same era.
Quantum circuit learning
Mitarai, K., Negoro, M., Kitagawa, M. & Fujii, K · 2018
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Bayesian searches and quantum oscillators
Chapline, G. & Otten, M · 2018
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Quantum supremacy using a programmable superconducting processor
Arute, F. et al · 2019
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Noise-resilient quantum dynamics using symmetry-preserving ansatzes
Otten, M., Cortes, C. L. & Gray, S. K · 2019
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Simulating quantum many-body dynamics on a current digital quantum computer
Smith, A., Kim, M., Pollmann, F. & Knolle, J · 2019
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Quantum hardware simulating four-dimensional inelastic neutron scattering
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Entanglement of two, three, or four plasmonically coupled quantum dots
Otten, M. et al · 2015
Cited alongside, same era.
Thermomechanical two-mode squeezing in an ultrahigh-q membrane resonator
Patil, Y., Chakram, S., Chang, L. & Vengalattore, M · 2015
Cited alongside, same era.
Scalable quantum simulation of molecular energies
O‘Malley, P. et al · 2016
Cited alongside, same era.
Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets
Kandala, A. et al · 2017
Cited alongside, same era.
Quantum machine learning
Biamonte, J. et al · 2017
Cited alongside, same era.
Error mitigation for short-depth quantum circuits
Temme, K., Bravyi, S. & Gambetta, J. M · 2017
Cited alongside, same era.
Chiesa, A. et al · 2019
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Supervised learning with quantum-enhanced feature spaces
Havliček, V. et al · 2019
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Quantum machine learning in feature hilbert spaces
Schuld, M. & Killoran, N · 2019
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Experimental kernel-based quantum machine learning in finite feature space (2019)
Bartkiewicz, K. et al · 2019
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Qiskit: An open-source framework for quantum computing (2019)
Abraham, H. et al · 2019
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Recovering noise-free quantum observables
Otten, M. & Gray, S. K · 2019
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Accounting for errors in quantum algorithms via individual error reduction
Otten, M. & Gray, S. K · 2019
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Error mitigation extends the computational reach of a noisy quantum processor
Kandala, A. et al · 2019
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Cost-function-dependent barren plateaus in shallow quantum neural networks
Cerezo, M., Sone, A., Volkoff, T., Cincio, L. & Coles, P. J · 2020
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QuaC: Open quantum systems in C, a time-dependent open quantum systems solver
Otten, M · 2020
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Reinforcement learning via gaussian processes with neural network dual kernels
Goumiri, I. R., Priest, B. W. & Schneider, M. D · 2020
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