| Variational Neural-Network Ansatz for Steady States in Open Quantum Systems F Vicentini, A Biella, N Regnault, C Ciuti Phys. Rev. Lett 122 (25), 250503, 2019 | 244 | 2019 |
| NetKet: A machine learning toolkit for many-body quantum systems D Hofmann, JET Smith, T Westerhout, F Alet, E Davis, S Efthymiou, ... SoftwareX 10, 100311, 2019 | 134* | 2019 |
| Critical slowing down in driven-dissipative Bose-Hubbard lattices F Vicentini, F Minganti, R Rota, G Orso, C Ciuti Physical Review A 97 (1), 013853, 2018 | 117 | 2018 |
| An efficient quantum algorithm for the time evolution of parameterized circuits S Barison, F Vicentini, G Carleo Quantum 5, 512, 2021 | 116 | 2021 |
| Netket 3: Machine learning toolbox for many-body quantum systems F Vicentini, D Hofmann, A Szabó, D Wu, C Roth, C Giuliani, G Pescia, ... SciPost Physics Codebases, 007, 2022 | 105 | 2022 |
| Modern applications of machine learning in quantum sciences A Dawid, J Arnold, B Requena, A Gresch, M Płodzień, K Donatella, ... arXiv preprint arXiv:2204.04198, 2022 | 72* | 2022 |
| Nonlinear Polariton Fluids in a Flatband Reveal Discrete Gap Solitons V Goblot, B Rauer, F Vicentini, A Le Boité, E Galopin, A Lemaître, ... Physical Review Letters 123 (11), 113901, 2019 | 59 | 2019 |
| mpi4jax: Zero-copy MPI communication of JAX arrays D Häfner, F Vicentini Journal of Open Source Software 6 (65), 3419, 2021 | 32 | 2021 |
| Variational Benchmarks for Quantum Many-Body Problems D Wu, R Rossi, F Vicentini, N Astrakhantsev, F Becca, X Cao, ... arXiv preprint arXiv:2302.04919, 2023 | 31 | 2023 |
| From tensor-network quantum states to tensorial recurrent neural networks D Wu, R Rossi, F Vicentini, G Carleo Physical Review Research 5 (3), L032001, 2023 | 24 | 2023 |
| Optimal stochastic unraveling of disordered open quantum systems: Application to driven-dissipative photonics lattices F Vicentini, F Minganti, A Biella, G Orso, C Ciuti Physical Review A 99 (1), 032115, 2019 | 24 | 2019 |
| Unbiasing time-dependent Variational Monte Carlo by projected quantum evolution A Sinibaldi, C Giuliani, G Carleo, F Vicentini Quantum 7, 1131, 2023 | 23 | 2023 |
| Variational dynamics as a ground-state problem on a quantum computer S Barison, F Vicentini, I Cirac, G Carleo Physical Review Research 4 (4), 043161, 2022 | 15 | 2022 |
| Positive-definite parametrization of mixed quantum states with deep neural networks F Vicentini, R Rossi, G Carleo arXiv preprint arXiv:2206.13488, 2022 | 15 | 2022 |
| Machine learning toolbox for quantum many body physics F Vicentini Nature Reviews Physics 3 (3), 156-156, 2021 | 9 | 2021 |
| Learning ground states of gapped quantum Hamiltonians with Kernel Methods C Giuliani, F Vicentini, R Rossi, G Carleo Quantum 7, 1096, 2023 | 8 | 2023 |
| Empirical sample complexity of neural network mixed state reconstruction H Zhao, G Carleo, F Vicentini Quantum 8, 1358, 2024 | 7 | 2024 |
| Embedding Classical Variational Methods in Quantum Circuits S Barison, F Vicentini, G Carleo arXiv preprint arXiv:2309.08666, 2023 | 3 | 2023 |
| Efficiency of neural quantum states in light of the quantum geometric tensor S Dash, F Vicentini, M Ferrero, A Georges arXiv preprint arXiv:2402.01565, 2024 | 1 | 2024 |
| Variational dynamics of open quantum systems in phase space D Eeltink, F Vicentini, V Savona arXiv preprint arXiv:2307.07429, 2023 | | 2023 |
Giuseppe CarleoAssociate Professor of Physics - EPFL, Lausanne, SwitzerlandVerified email at epfl.ch
