| Parameterized quantum circuits as machine learning models M Benedetti, E Lloyd, S Sack, M Fiorentini Quantum Science and Technology 4 (4), 043001, 2019 | 790 | 2019 |
| Hardware-efficient variational quantum algorithms for time evolution M Benedetti, M Fiorentini, M Lubasch Physical Review Research 3 (3), 033083, 2021 | 119 | 2021 |
| Filtering variational quantum algorithms for combinatorial optimization D Amaro, C Modica, M Rosenkranz, M Fiorentini, M Benedetti, M Lubasch Quantum Science and Technology 7 (1), 015021, 2022 | 95 | 2022 |
| Thermoelectric coefficients of n -doped silicon from first principles via the solution of the Boltzmann transport equation M Fiorentini, N Bonini Physical Review B 94 (8), 085204, 2016 | 95 | 2016 |
| A case study of variational quantum algorithms for a job shop scheduling problem D Amaro, M Rosenkranz, N Fitzpatrick, K Hirano, M Fiorentini EPJ Quantum Technology 9 (1), 5, 2022 | 54 | 2022 |
| Variational quantum amplitude estimation K Plekhanov, M Rosenkranz, M Fiorentini, M Lubasch Quantum 6, 670, 2022 | 42 | 2022 |
| Variational inference with a quantum computer M Benedetti, B Coyle, M Fiorentini, M Lubasch, M Rosenkranz Physical Review Applied 16 (4), 044057, 2021 | 36 | 2021 |
| Erratum: parameterized quantu m circuits as machine learning models (2019 Quant. Sci. Tech. 4 043001) M Benedetti, E Lloyd, S Sack, M Fiorentini Quantu m Science and Technology 5 (1), 019601, 2019 | 11 | 2019 |
| Parameterized quantum circuits as machine learning models. Quantum Science and Technology 4 (4), 043001 (2019) M Benedetti, E Lloyd, S Sack, M Fiorentini | 5 | |
| Circuitos cuánticos parametrizados como modelos de aprendizaje automático M Benedetti, E Lloyd, S Sack, M Fiorentini Ciencia y tecnología cuánticas 4 (4), 043001, 2019 | 3 | 2019 |
| Computer system and method for utilizing variational inference M Benedetti, BJ Coyle, M Fiorentini, M Lubasch, M Rosenkranz US Patent App. 17/654,225, 2022 | 2 | 2022 |
| Parametrerade kvantkretsar som maskininlärningsmodeller M Benedetti, E Lloyd, S Sack, M Fiorentini Quantum Science and Technology 4 (4), 043001, 2019 | 2 | 2019 |
| Parameterized quantum circuits as machine learning models. Quantum Science and Technology 4 (4): 043001, DOI: 10.1088/2058-9565/ab4eb5 M Benedetti, E Lloyd, S Sack, M Fiorentini arXiv preprint arXiv:1906.07682, 2019 | 2 | 2019 |
| Hardware-efficient variational quantum algorithms for time evolution (2020) M Benedetti, M Fiorentini, M Lubasch arXiv preprint arXiv:2009.12361, 0 | 2 | |
| Apparatus And Method For Optimizing, Monitoring And Controlling A Real Physical System L Coopmans, Y Kikuchi, M Benedetti, M Fiorentini US Patent App. 18/201,410, 2023 | | 2023 |
| Method for reducing quantum circuit depth for amplitude estimation M Rosenkranz, M Lubasch, M Fiorentini, K Plekhanov US Patent App. 17/930,339, 2023 | | 2023 |
| Quantum computer system and method for combinatorial optimization D Amaro, C Modica, M Benedetti, M Fiorentini, M Lubasch, ... US Patent App. 17/825,908, 2022 | | 2022 |
| Parameterized quantum circuits as machine learning models (vol 4, 043001, 2019) M Benedetti, E Lloyd, S Sack, M Fiorentini QUANTUM SCIENCE AND TECHNOLOGY 5 (1), 2020 | | 2020 |
| Stefan Sack en Mattia Fiorentini," M Benedetti, E Lloyd Geparametriseerde kwantumcircuits als modellen voor machine learning …, 2019 | | 2019 |
| downloaded from the King’s Research Portal at https://kclpure. kcl. ac. uk/portal C Piacentini | | 2015 |
Marcello BenedettiQuantinuumVerified email at quantinuum.com
