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Fermionic neural-network states for ab-initio electronic structure

Nature communications, 2020-05, Vol.11 (1), p.2368-2368, Article 2368

2020

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Neural-Network Approach to Dissipative Quantum Many-Body Dynamics

Physical review letters, 2019-06, Vol.122 (25), p.250502-250502, Article 250502

2019

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Constructing exact representations of quantum many-body systems with deep neural networks

Nature communications, 2018-12, Vol.9 (1), p.5322-11, Article 5322

2018

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Classical variational simulation of the Quantum Approximate Optimization Algorithm

npj quantum information, 2021-06, Vol.7 (1), p.1-7, Article 101

2021

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Quantum Natural Gradient

Quantum (Vienna, Austria), 2020-05, Vol.4, p.269, Article 269

2020

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Deep Learning the Hohenberg-Kohn Maps of Density Functional Theory

Physical review letters, 2020-08, Vol.125 (7), p.1-076402, Article 076402

2020

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Restricted Boltzmann machines in quantum physics

Nature physics, 2019-09, Vol.15 (9), p.887-892

2019

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Spreading of correlations in exactly solvable quantum models with long-range interactions in arbitrary dimensions

New journal of physics, 2016-09, Vol.18 (9), p.93002

2016

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An efficient quantum algorithm for the time evolution of parameterized circuits

Quantum (Vienna, Austria), 2021-07, Vol.5, p.512, Article 512

2021

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Precise measurement of quantum observables with neural-network estimators

Physical review research, 2020-06, Vol.2 (2), Article 022060

2020

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Quantum process tomography with unsupervised learning and tensor networks

Nature communications, 2023-05, Vol.14 (1), p.2858-2858, Article 2858

2023

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Solving the quantum many-body problem with artificial neural networks

Science (American Association for the Advancement of Science), 2017-02, Vol.355 (6325), p.602-606

2017

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Broken-Symmetry Ground States of the Heisenberg Model on the Pyrochlore Lattice

Physical review. X, 2021-10, Vol.11 (4), p.041021, Article 041021

2021

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Nuclei with Up to A=6 Nucleons with Artificial Neural Network Wave Functions

Few-body systems, 2022-03, Vol.63 (1)

2022

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Simultaneous Perturbation Stochastic Approximation of the Quantum Fisher Information

Quantum (Vienna, Austria), 2021-10, Vol.5, p.567, Article 567

2021

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Hidden-nucleons neural-network quantum states for the nuclear many-body problem

Physical review research, 2022-12, Vol.4 (4), Article 043178

2022

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Ground state phase diagram of the one-dimensional Bose-Hubbard model from restricted Boltzmann machines

Journal of physics. Conference series, 2019-10, Vol.1290 (1), p.12005

2019

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Neural-network quantum states for periodic systems in continuous space

Physical review research, 2022-05, Vol.4 (2), Article 023138

2022

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Unitary Dynamics of Strongly Interacting Bose Gases with the Time-Dependent Variational Monte Carlo Method in Continuous Space

Physical review. X, 2017-08, Vol.7 (3), p.031026, Article 031026

2017

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Nonstoquastic Hamiltonians and quantum annealing of an Ising spin glass

Physical review. B, 2017-05, Vol.95 (18), p.184416, Article 184416

2017

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Variational solutions to fermion-to-qubit mappings in two spatial dimensions

Quantum (Vienna, Austria), 2022-10, Vol.6, p.833, Article 833

2022

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Unbiased Monte Carlo cluster updates with autoregressive neural networks

Physical review research, 2021-11, Vol.3 (4), Article L042024

2021

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Learning ground states of gapped quantum Hamiltonians with Kernel Methods

Quantum (Vienna, Austria), 2023-08, Vol.7, p.1096, Article 1096

2023

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Unbiasing time-dependent Variational Monte Carlo by projected quantum evolution

Quantum (Vienna, Austria), 2023-10, Vol.7, p.1131, Article 1131

2023

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Fermionic neural-network states for ab-initio electronic structure

Neural-Network Approach to Dissipative Quantum Many-Body Dynamics

Constructing exact representations of quantum many-body systems with deep neural networks

Classical variational simulation of the Quantum Approximate Optimization Algorithm

Quantum Natural Gradient

Deep Learning the Hohenberg-Kohn Maps of Density Functional Theory

Restricted Boltzmann machines in quantum physics

Spreading of correlations in exactly solvable quantum models with long-range interactions in arbitrary dimensions

An efficient quantum algorithm for the time evolution of parameterized circuits

Precise measurement of quantum observables with neural-network estimators

Quantum process tomography with unsupervised learning and tensor networks

Solving the quantum many-body problem with artificial neural networks

Broken-Symmetry Ground States of the Heisenberg Model on the Pyrochlore Lattice

Nuclei with Up to A=6 Nucleons with Artificial Neural Network Wave Functions

Simultaneous Perturbation Stochastic Approximation of the Quantum Fisher Information

Hidden-nucleons neural-network quantum states for the nuclear many-body problem

Quantum Simulators: Architectures and Opportunities

Ground state phase diagram of the one-dimensional Bose-Hubbard model from restricted Boltzmann machines

Neural-network quantum states for periodic systems in continuous space

Unitary Dynamics of Strongly Interacting Bose Gases with the Time-Dependent Variational Monte Carlo Method in Continuous Space

Nonstoquastic Hamiltonians and quantum annealing of an Ising spin glass

Variational solutions to fermion-to-qubit mappings in two spatial dimensions

Unbiased Monte Carlo cluster updates with autoregressive neural networks

Learning ground states of gapped quantum Hamiltonians with Kernel Methods

Unbiasing time-dependent Variational Monte Carlo by projected quantum evolution

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