Related references
Note: Only part of the references are listed.Layerwise learning for quantum neural networks
Andrea Skolik et al.
QUANTUM MACHINE INTELLIGENCE (2021)
Variational quantum unsampling on a quantum photonic processor
Jacques Carolan et al.
NATURE PHYSICS (2020)
Noise resilience of variational quantum compiling
Kunal Sharma et al.
NEW JOURNAL OF PHYSICS (2020)
Machine learning enabled autonomous microstructural characterization in 3D samples
Henry Chan et al.
NPJ COMPUTATIONAL MATERIALS (2020)
On the universality of the quantum approximate optimization algorithm
M. E. S. Morales et al.
QUANTUM INFORMATION PROCESSING (2020)
Certified variational quantum algorithms for eigenstate preparation
Andrey Kardashin et al.
PHYSICAL REVIEW A (2020)
Variational quantum eigensolver for frustrated quantum systems
Alexey Uvarov et al.
PHYSICAL REVIEW B (2020)
Machine learning phase transitions with a quantum processor
A. Uvarov et al.
PHYSICAL REVIEW A (2020)
Variational quantum algorithms for dimensionality reduction and classification
Jin-Min Liang et al.
PHYSICAL REVIEW A (2020)
A generative modeling approach for benchmarking and training shallow quantum circuits
Marcello Benedetti et al.
NPJ QUANTUM INFORMATION (2019)
Quantum supremacy using a programmable superconducting processor
Frank Arute et al.
NATURE (2019)
Contextuality Test of the Nonclassicality of Variational Quantum Eigensolvers
William M. Kirby et al.
PHYSICAL REVIEW LETTERS (2019)
Simulating quantum many-body dynamics on a current digital quantum computer
Adam Smith et al.
NPJ QUANTUM INFORMATION (2019)
Quantum chemistry as a benchmark for near-term quantum computers
Alexander J. McCaskey et al.
NPJ QUANTUM INFORMATION (2019)
Parameterized quantum circuits as machine learning models
Marcello Benedetti et al.
QUANTUM SCIENCE AND TECHNOLOGY (2019)
Variational Quantum Computation of Excited States
Oscar Higgott et al.
QUANTUM (2019)
Quantum-assisted quantum compiling
Sumeet Khatri et al.
QUANTUM (2019)
AN INITIALIZATION STRATEGY FOR ADDRESSING BARREN PLATEAUS IN PARAMETRIZED QUANTUM CIRCUITS
Edward Grant et al.
QUANTUM (2019)
Evaluating analytic gradients on quantum hardware
Maria Schuld et al.
PHYSICAL REVIEW A (2019)
Computation of Molecular Spectra on a Quantum Processor with an Error-Resilient Algorithm
J. I. Colless et al.
PHYSICAL REVIEW X (2018)
Adequacy of Si:P chains as Fermi-Hubbard simulators
Amintor Dusko et al.
NPJ QUANTUM INFORMATION (2018)
Quantum Chemistry Calculations on a Trapped-Ion Quantum Simulator
Cornelius Hempel et al.
PHYSICAL REVIEW X (2018)
Barren plateaus in quantum neural network training landscapes
Jarrod R. McClean et al.
NATURE COMMUNICATIONS (2018)
Quantum optimization using variational algorithms on near-term quantum devices
Nikolaj Moll et al.
QUANTUM SCIENCE AND TECHNOLOGY (2018)
Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets
Abhinav Kandala et al.
NATURE (2017)
The theory of variational hybrid quantum-classical algorithms
Jarrod R. McClean et al.
NEW JOURNAL OF PHYSICS (2016)
Scalable Quantum Simulation of Molecular Energies
P. J. J. O'Malley et al.
PHYSICAL REVIEW X (2016)
A variational eigenvalue solver on a photonic quantum processor
Alberto Peruzzo et al.
NATURE COMMUNICATIONS (2014)
From transistor to trapped-ion computers for quantum chemistry
M. -H. Yung et al.
SCIENTIFIC REPORTS (2014)
Share Paper
