| Active learning machine learns to create new quantum experiments AA Melnikov, H Poulsen Nautrup, M Krenn, V Dunjko, M Tiersch, ... Proceedings of the National Academy of Sciences 115 (6), 1221-1226, 2018 | 341 | 2018 |
| Optimizing quantum error correction codes with reinforcement learning HP Nautrup, N Delfosse, V Dunjko, HJ Briegel, N Friis Quantum 3, 215, 2019 | 185 | 2019 |
| Quantum machine learning beyond kernel methods S Jerbi, LJ Fiderer, H Poulsen Nautrup, JM Kübler, HJ Briegel, V Dunjko Nature Communications 14 (1), 1-8, 2023 | 149 | 2023 |
| Entangling logical qubits with lattice surgery A Erhard, H Poulsen Nautrup, M Meth, L Postler, R Stricker, M Stadler, ... Nature 589 (7841), 220-224, 2021 | 135 | 2021 |
| Computationally universal phase of quantum matter R Raussendorf, C Okay, DS Wang, DT Stephen, HP Nautrup Physical review letters 122 (9), 090501, 2019 | 103 | 2019 |
| Subsystem symmetries, quantum cellular automata, and computational phases of quantum matter DT Stephen, HP Nautrup, J Bermejo-Vega, J Eisert, R Raussendorf Quantum 3, 142, 2019 | 94 | 2019 |
| Quantum enhancements for deep reinforcement learning in large spaces S Jerbi, LM Trenkwalder, H Poulsen Nautrup, HJ Briegel, V Dunjko PRX Quantum 2 (1), 010328, 2021 | 68 | 2021 |
| Fault-tolerant interface between quantum memories and quantum processors H Poulsen Nautrup, N Friis, HJ Briegel Nature communications 8 (1), 1321, 2017 | 53 | 2017 |
| Symmetry-protected topologically ordered states for universal quantum computation HP Nautrup, TC Wei Physical Review A 92 (5), 052309, 2015 | 43 | 2015 |
| Photonic architecture for reinforcement learning F Flamini, A Hamann, S Jerbi, LM Trenkwalder, HP Nautrup, HJ Briegel New Journal of Physics 22 (4), 045002, 2020 | 35 | 2020 |
| Operationally meaningful representations of physical systems in neural networks HP Nautrup, T Metger, R Iten, S Jerbi, LM Trenkwalder, H Wilming, ... Machine Learning: Science and Technology 3 (4), 045025, 2022 | 28 | 2022 |
| Symmetry-enriched topological order from partially gauging symmetry-protected topologically ordered states assisted by measurements Y Li, H Sukeno, AP Mana, HP Nautrup, TC Wei Physical Review B 108 (11), 115144, 2023 | 12 | 2023 |
| A framework for deep energy-based reinforcement learning with quantum speed-up S Jerbi, H Poulsen Nautrup, LM Trenkwalder, B Dunjko arXiv preprint arXiv:1910.12760, 2019 | 9 | 2019 |
| Quantum machine learning beyond kernel methods. Nat Commun 14 S Jerbi, LJ Fiderer, HP Nautrup, JM Kübler, HJ Briegel, V Dunjko | 7 | 2023 |
| Variational measurement-based quantum computation for generative modeling A Majumder, M Krumm, T Radkohl, HP Nautrup, S Jerbi, HJ Briegel arXiv preprint arXiv:2310.13524, 2023 | 5 | 2023 |
| Hybrid discrete-continuous compilation of trapped-ion quantum circuits with deep reinforcement learning F Preti, M Schilling, S Jerbi, LM Trenkwalder, HP Nautrup, F Motzoi, ... Quantum 8, 1343, 2024 | 4 | 2024 |
| Parity Quantum Computing as -Plane Measurement-Based Quantum Computing ID Smith, HP Nautrup, HJ Briegel Physical Review Letters 132 (22), 220602, 2024 | 2 | 2024 |
| Measurement-based quantum computation from Clifford quantum cellular automata HP Nautrup, HJ Briegel arXiv preprint arXiv:2312.13185, 2023 | 2 | 2023 |
| Automated Gadget Discovery in Science LM Trenkwalder, AL Incera, HP Nautrup, F Flamini, HJ Briegel arXiv preprint arXiv:2212.12743, 2022 | 2 | 2022 |
| Automated gadget discovery in the quantum domain LM Trenkwalder, A López-Incera, HP Nautrup, F Flamini, HJ Briegel Machine Learning: Science and Technology 4 (3), 035043, 2023 | 1 | 2023 |
Hans J BriegelProfessor of Theoretical Physics, University of InnsbruckVerified email at uibk.ac.at
