| Tensorflow quantum: A software framework for quantum machine learning M Broughton, G Verdon, T McCourt, AJ Martinez, JH Yoo, SV Isakov, ... arXiv preprint arXiv:2003.02989, 2020 | 416 | 2020 |
| Challenges and opportunities in quantum machine learning M Cerezo, G Verdon, HY Huang, L Cincio, PJ Coles Nature Computational Science 2 (9), 567-576, 2022 | 377 | 2022 |
| Quantum Graph Neural Networks G Verdon, T McCourt, E Luzhnica, V Singh, S Leichenauer, J Hidary arXiv preprint arXiv:1909.12264, 2019 | 320* | 2019 |
| Learning to learn with quantum neural networks via classical neural networks G Verdon, M Broughton, JR McClean, KJ Sung, R Babbush, Z Jiang, ... arXiv preprint arXiv:1907.05415, 2019 | 217 | 2019 |
| Group-invariant quantum machine learning M Larocca, F Sauvage, FM Sbahi, G Verdon, PJ Coles, M Cerezo PRX Quantum 3 (3), 030341, 2022 | 146 | 2022 |
| A universal training algorithm for quantum deep learning G Verdon, J Pye, M Broughton arXiv preprint arXiv:1806.09729, 2018 | 132 | 2018 |
| A quantum algorithm to train neural networks using low-depth circuits G Verdon, M Broughton, J Biamonte arXiv preprint arXiv:1712.05304, 2017 | 108 | 2017 |
| Quantum Hamiltonian-based models and the variational quantum thermalizer algorithm G Verdon, J Marks, S Nanda, S Leichenauer, J Hidary arXiv preprint arXiv:1910.02071, 2019 | 95 | 2019 |
| A semi-agnostic ansatz with variable structure for quantum machine learning M Bilkis, M Cerezo, G Verdon, PJ Coles, L Cincio arXiv preprint arXiv:2103.06712, 2021 | 62 | 2021 |
| Tensorflow quantum: a software framework for quantum machine learning. 2020 M Broughton, G Verdon, T McCourt, AJ Martinez, JH Yoo, SV Isakov, ... arXiv preprint arXiv:2003.02989, 2003 | 44 | 2003 |
| A quantum approximate optimization algorithm for continuous problems G Verdon, JM Arrazola, K Brádler, N Killoran arXiv preprint arXiv:1902.00409, 2019 | 42 | 2019 |
| Quantum repeater from quantum analog-digital interconverter G Verdon-Akzam US Patent 11,526,797, 2022 | 28 | 2022 |
| Tensorflow quantum: A software framework for quantum machine learning. arXiv 2020 M Broughton, G Verdon, T McCourt, AJ Martinez, JH Yoo, SV Isakov, ... arXiv preprint arXiv:2003.02989, 2003 | 27 | 2003 |
| Quantum hamiltonian-based models and the variational quantum thermalizer algorithm (2019) G Verdon, J Marks, S Nanda, S Leichenauer, J Hidary arXiv preprint arXiv:1910.02071 25, 1910 | 21 | 1910 |
| Asymptotically limitless quantum energy teleportation via qudit probes G Verdon-Akzam, E Martin-Martinez, A Kempf Phys. Rev. A 93 (2), 022308, 2016 | 20 | 2016 |
| A semi-agnostic ansatz with variable structure for variational quantum algorithms M Bilkis, M Cerezo, G Verdon, PJ Coles, L Cincio Quantum Machine Intelligence 5 (2), 43, 2023 | 15 | 2023 |
| A quantum algorithm to train neural networks using low-depth circuits (2017) G Verdon, M Broughton, J Biamonte arXiv preprint arXiv:1712.05304, 2017 | 11 | 2017 |
| Provably efficient variational generative modeling of quantum many-body systems via quantum-probabilistic information geometry FM Sbahi, AJ Martinez, S Patel, D Saberi, JH Yoo, G Roeder, G Verdon arXiv preprint arXiv:2206.04663, 2022 | 10 | 2022 |
| From long-distance entanglement to building a nationwide quantum internet: Report of the DOE quantum internet blueprint workshop D Awschalom Brookhaven National Lab.(BNL), Upton, NY (United States), 2020 | 10 | 2020 |
| Quantum analog-digital interconversion for encoding and decoding quantum signals G Verdon-Akzam US Patent 11,308,415, 2022 | 6 | 2022 |
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