Vedran Dunjko

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Hans J BriegelProfessor of Theoretical Physics, University of InnsbruckVerified email at uibk.ac.at
Erika AnderssonInstitute of Photonics and Quantum Sciences, Heriot-Watt University, Edinburgh, UKVerified email at hw.ac.uk
Jacob TaylorJoint Center for Quantum Information and Computer Science; Joint Quantum Institute; NISTVerified email at umd.edu
Nicolai FriisInstitute of Atomic and Subatomic Physics (Atominstitut), TU WienVerified email at tuwien.ac.at
Elham KashefiNQCC, CNRS (LIP6) and University of Edinburgh (Informatics)Verified email at inf.ed.ac.uk
Thomas BäckProfessor of Computer Science, Leiden University; Chief Scientist, NORCE Research Centre, NorwayVerified email at liacs.leidenuniv.nl
Hendrik Poulsen NautrupUniversität InnsbruckVerified email at uibk.ac.at
Petros WalldenThe University of EdinburghVerified email at ed.ac.uk
Gerald BullerHeriot-Watt UniversityVerified email at hw.ac.uk
John JeffersProfessor, University of StrathclydeVerified email at strath.ac.uk
Robert John CollinsLeonardoVerified email at leonardocompany.com
Wolfgang DürProfessor of Theoretical Physics, University of InnsbruckVerified email at uibk.ac.at
Jordi Tura i BruguésApplied Quantum Algorithms Leiden, Leiden UniversityVerified email at lorentz.leidenuniv.nl
Joseph FitzsimonsHorizon Quantum ComputingVerified email at horizonquantum.com
Philip WaltherProfessor of Physics, University of ViennaVerified email at univie.ac.at
Anton ZeilingerUniversity of ViennaVerified email at univie.ac.at
Tomoyuki MorimaeAssociate Professor, Yukawa Institute for Theoretical Physics, Kyoto UniversityVerified email at yukawa.kyoto-u.ac.jp
Anthony LeverrierInriaVerified email at inria.fr
Renato RennerProfessor for Theoretical Physics, ETH ZurichVerified email at ethz.ch
Peter WittekUniversity of TorontoVerified email at peterwittek.com

Vedran Dunjko

Leiden University

Verified email at liacs.leidenuniv.nl

Quantum computing AI


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Machine learning & artificial intelligence in the quantum domain: a review of recent progress V Dunjko, HJ Briegel Reports on Progress in Physics 81 (7), 074001, 2018	1069	2018
On the convergence of projective-simulation–based reinforcement learning in Markov decision processes WL Boyajian, J Clausen, LM Trenkwalder, V Dunjko, HJ Briegel Quantum machine intelligence 2, 1-21, 2020	810	2020
Quantum-enhanced machine learning V Dunjko, JM Taylor, HJ Briegel Physical review letters 117 (13), 130501, 2016	483	2016
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	413	2020
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	346	2018
Quantum speedup for active learning agents GD Paparo, V Dunjko, A Makmal, MA Martin-Delgado, HJ Briegel Physical Review X 4 (3), 031002, 2014	260	2014
Quantum digital signatures without quantum memory V Dunjko, P Wallden, E Andersson Physical review letters 112 (4), 040502, 2014	217	2014
Optimizing quantum error correction codes with reinforcement learning HP Nautrup, N Delfosse, V Dunjko, HJ Briegel, N Friis Quantum 3, 215, 2019	188	2019
Experimental quantum speed-up in reinforcement learning agents V Saggio, BE Asenbeck, A Hamann, T Strömberg, P Schiansky, V Dunjko, ... Nature 591 (7849), 229-233, 2021	173	2021
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	165	2023
Experimental demonstration of quantum digital signatures using phase-encoded coherent states of light PJ Clarke, RJ Collins, V Dunjko, E Andersson, J Jeffers, GS Buller Nature communications 3 (1), 1174, 2012	165	2012
Quantum agents in the gym: a variational quantum algorithm for deep q-learning A Skolik, S Jerbi, V Dunjko Quantum 6, 720, 2022	159	2022
Parametrized quantum policies for reinforcement learning S Jerbi, C Gyurik, S Marshall, H Briegel, V Dunjko Advances in Neural Information Processing Systems 34, 28362-28375, 2021	155	2021
Reinforcement learning for optimization of variational quantum circuit architectures M Ostaszewski, LM Trenkwalder, W Masarczyk, E Scerri, V Dunjko Advances in Neural Information Processing Systems 34, 18182-18194, 2021	140	2021
Quantum digital signatures with quantum-key-distribution components P Wallden, V Dunjko, A Kent, E Andersson Physical Review A 91 (4), 042304, 2015	133	2015
Blind quantum computing with weak coherent pulses V Dunjko, E Kashefi, A Leverrier Physical review letters 108 (20), 200502, 2012	124	2012
Composable security of delegated quantum computation V Dunjko, JF Fitzsimons, C Portmann, R Renner Advances in Cryptology–ASIACRYPT 2014: 20th International Conference on the …, 2014	107	2014
A non-review of quantum machine learning: trends and explorations V Dunjko, P Wittek Quantum Views 4, 32, 2020	99	2020
Performance comparison of optimization methods on variational quantum algorithms X Bonet-Monroig, H Wang, D Vermetten, B Senjean, C Moussa, T Bäck, ... Physical Review A 107 (3), 032407, 2023	95	2023
Experimental demonstration of kilometer-range quantum digital signatures RJ Donaldson, RJ Collins, K Kleczkowska, R Amiri, P Wallden, V Dunjko, ... Physical Review A 93 (1), 012329, 2016	94	2016

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