Giuseppe Carleo

Orcid: 0000-0002-8887-4356

According to our database1, Giuseppe Carleo authored at least 24 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Online presence:

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Bibliography

2024
Ab-initio variational wave functions for the time-dependent many-electron Schrödinger equation.
CoRR, 2024

2023
A rapidly mixing Markov chain from any gapped quantum many-body system.
Quantum, November, 2023

Unbiasing time-dependent Variational Monte Carlo by projected quantum evolution.
Quantum, October, 2023

Learning ground states of gapped quantum Hamiltonians with Kernel Methods.
Quantum, August, 2023

Continuous-variable neural network quantum states and the quantum rotor model.
Quantum Mach. Intell., June, 2023

Hybrid Ground-State Quantum Algorithms based on Neural Schrödinger Forging.
CoRR, 2023

Empirical Sample Complexity of Neural Network Mixed State Reconstruction.
CoRR, 2023

Stochastic Approximation of Variational Quantum Imaginary Time Evolution.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

2022
Variational solutions to fermion-to-qubit mappings in two spatial dimensions.
Quantum, September, 2022

Ab-initio quantum chemistry with neural-network wavefunctions.
CoRR, 2022

Positive-definite parametrization of mixed quantum states with deep neural networks.
CoRR, 2022

From Tensor Network Quantum States to Tensorial Recurrent Neural Networks.
CoRR, 2022

2021
Simultaneous Perturbation Stochastic Approximation of the Quantum Fisher Information.
Quantum, 2021

An efficient quantum algorithm for the time evolution of parameterized circuits.
Quantum, 2021

Natural evolution strategies and variational Monte Carlo.
Mach. Learn. Sci. Technol., 2021

NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems.
CoRR, 2021

Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks.
CoRR, 2021

Neural tensor contractions and the expressive power of deep neural quantum states.
CoRR, 2021

2020
Quantum Natural Gradient.
Quantum, 2020

Gauge equivariant neural networks for quantum lattice gauge theories.
CoRR, 2020

Phases of two-dimensional spinless lattice fermions with first-quantized deep neural-network quantum states.
CoRR, 2020

Natural evolution strategies and quantum approximate optimization.
CoRR, 2020

2019
NetKet: A machine learning toolkit for many-body quantum systems.
SoftwareX, 2019

Deep autoregressive models for the efficient variational simulation of many-body quantum systems.
CoRR, 2019


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