default search action
Vedran Dunjko
Person information
- affiliation: Leiden University, The Netherlands
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [j20]Charles Moussa
, Yash J. Patel
Hyperparameter importance and optimization of quantum neural networks across small datasets. Mach. Learn. 113(4): 1941-1966 (2024) - [j19]Elies Gil-Fuster
On the expressivity of embedding quantum kernels. Mach. Learn. Sci. Technol. 5(2): 25003 (2024) - [c14]Yash J. Patel, Akash Kundu, Mateusz Ostaszewski, Xavier Bonet-Monroig, Vedran Dunjko, Onur Danaci:
Curriculum reinforcement learning for quantum architecture search under hardware errors. ICLR 2024 - [c13]Marie C. Kempkes
Reliable Classifications with Guaranteed Confidence Using the Dempster-Shafer Theory of Evidence. ECML/PKDD (2) 2024: 89-105 - [i43]Yash J. Patel, Akash Kundu, Mateusz Ostaszewski, Xavier Bonet-Monroig, Vedran Dunjko, Onur Danaci:
Curriculum reinforcement learning for quantum architecture search under hardware errors. CoRR abs/2402.03500 (2024) - [i42]Simon C. Marshall, Casper Gyurik, Vedran Dunjko:
On Bounded Advice Classes. CoRR abs/2405.18155 (2024) - [i41]Elies Gil-Fuster, Casper Gyurik, Adrián Pérez-Salinas, Vedran Dunjko:
On the relation between trainability and dequantization of variational quantum learning models. CoRR abs/2406.07072 (2024) - [i40]Simon C. Marshall, Scott Aaronson, Vedran Dunjko:
Improved separation between quantum and classical computers for sampling and functional tasks. CoRR abs/2410.20935 (2024) - [i39]Casper Gyurik, Alexander Schmidhuber, Robbie King, Vedran Dunjko, Ryu Hayakawa:
Quantum computing and persistence in topological data analysis. CoRR abs/2410.21258 (2024) - 2023
- [j18]Casper Gyurik
Structural risk minimization for quantum linear classifiers. Quantum 7: 893 (2023) - [j17]Mathys Rennela, Sebastiaan Brand
Hybrid divide-and-conquer approach for tree search algorithms. Quantum 7: 959 (2023) - [j16]Simon C. Marshall, Casper Gyurik, Vedran Dunjko:
High Dimensional Quantum Machine Learning With Small Quantum Computers. Quantum 7: 1078 (2023) - [j15]Lieuwe Vinkhuijzen
LIMDD: A Decision Diagram for Simulation of Quantum Computing Including Stabilizer States. Quantum 7: 1108 (2023) - [c12]Alice Barthe
Continuous Variables Quantum Algorithm for Solving Ordinary Differential Equations. QCE 2023: 48-53 - [c11]Waheeda Saib, Xavier Bonet-Monroig, Vedran Dunjko, Ivano Tavernelli, Thomas Bäck, Hao Wang:
Benchmarking Adaptive Quantum Circuit Optimization Algorithms for Quantum Chemistry. QCE 2023: 83-88 - [c10]Charles Moussa, Hao Wang, Mauricio Araya-Polo, Thomas Bäck, Vedran Dunjko:
Application of quantum-inspired generative models to small molecular datasets. QCE 2023: 342-348 - [c9]Sofiène Jerbi, Arjan Cornelissen, Maris Ozols
Quantum Policy Gradient Algorithms. TQC 2023: 13:1-13:24 - [i38]Charles Moussa, Hao Wang, Mauricio Araya-Polo, Thomas Bäck, Vedran Dunjko:
Application of quantum-inspired generative models to small molecular datasets. CoRR abs/2304.10867 (2023) - [i37]Sofiène Jerbi, Casper Gyurik, Simon C. Marshall, Riccardo Molteni, Vedran Dunjko:
Shadows of quantum machine learning. CoRR abs/2306.00061 (2023) - [i36]Akash Kundu, Przemyslaw Bedelek, Mateusz Ostaszewski, Onur Danaci, Yash J. Patel, Vedran Dunjko, Jaroslaw Adam Miszczak:
Enhancing variational quantum state diagonalization using reinforcement learning techniques. CoRR abs/2306.11086 (2023) - [i35]Casper Gyurik, Vedran Dunjko:
Exponential separations between classical and quantum learners. CoRR abs/2306.16028 (2023) - [i34]Elies Gil-Fuster, Jens Eisert, Vedran Dunjko:
On the expressivity of embedding quantum kernels. CoRR abs/2309.14419 (2023) - [i33]Lea M. Trenkwalder, Eleanor Scerri, Thomas E. O'Brien, Vedran Dunjko:
Compilation of product-formula Hamiltonian simulation via reinforcement learning. CoRR abs/2311.04285 (2023) - 2022
- [j14]Andrea Skolik, Sofiène Jerbi, Vedran Dunjko:
Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning. Quantum 6: 720 (2022) - [j13]Casper Gyurik
Towards quantum advantage via topological data analysis. Quantum 6: 855 (2022) - [c8]Charles Moussa
Hyperparameter Importance of Quantum Neural Networks Across Small Datasets. DS 2022: 32-46 - [i32]Simon C. Marshall, Casper Gyurik, Vedran Dunjko:
High Dimensional Quantum Learning With Small Quantum Computers. CoRR abs/2203.13739 (2022) - [i31]Andrea Skolik, Michele Cattelan, Sheir Yarkoni, Thomas Bäck, Vedran Dunjko:
Equivariant quantum circuits for learning on weighted graphs. CoRR abs/2205.06109 (2022) - [i30]Charles Moussa, Jan N. van Rijn, Thomas Bäck, Vedran Dunjko:
Hyperparameter Importance of Quantum Neural Networks Across Small Datasets. CoRR abs/2206.09992 (2022) - [i29]Yash J. Patel
Reinforcement Learning Assisted Recursive QAOA. CoRR abs/2207.06294 (2022) - [i28]Casper Gyurik, Vedran Dunjko:
On establishing learning separations between classical and quantum machine learning with classical data. CoRR abs/2208.06339 (2022) - [i27]Sofiène Jerbi, Arjan Cornelissen, Maris Ozols, Vedran Dunjko:
Quantum policy gradient algorithms. CoRR abs/2212.09328 (2022) - 2021
- [j12]Valeria Saggio
Experimental quantum speed-up in reinforcement learning agents. Nat. 591(7849): 229-233 (2021) - [j11]Zhikuan Zhao
Smooth input preparation for quantum and quantum-inspired machine learning. Quantum Mach. Intell. 3(1): 1-6 (2021) - [j10]Arne Hamann
Quantum-accessible reinforcement learning beyond strictly epochal environments. Quantum Mach. Intell. 3(2): 1-18 (2021) - [j9]Saad Yalouz
Encoding strongly-correlated many-boson wavefunctions on a photonic quantum computer: application to the attractive Bose-Hubbard model. Quantum 5: 572 (2021) - [j8]Davide Orsucci
On solving classes of positive-definite quantum linear systems with quadratically improved runtime in the condition number. Quantum 5: 573 (2021) - [c7]Charles Moussa
Tabu-Driven Quantum Neighborhood Samplers. EvoCOP 2021: 100-119 - [c6]Mateusz Ostaszewski, Lea M. Trenkwalder, Wojciech Masarczyk, Eleanor Scerri, Vedran Dunjko:
Reinforcement learning for optimization of variational quantum circuit architectures. NeurIPS 2021: 18182-18194 - [c5]Sofiène Jerbi, Casper Gyurik, Simon C. Marshall, Hans J. Briegel, Vedran Dunjko:
Parametrized Quantum Policies for Reinforcement Learning. NeurIPS 2021: 28362-28375 - [i26]Sofiène Jerbi, Casper Gyurik, Simon C. Marshall, Hans J. Briegel, Vedran Dunjko:
Variational quantum policies for reinforcement learning. CoRR abs/2103.05577 (2021) - [i25]Mateusz Ostaszewski, Lea M. Trenkwalder, Wojciech Masarczyk, Eleanor Scerri, Vedran Dunjko:
Reinforcement learning for optimization of variational quantum circuit architectures. CoRR abs/2103.16089 (2021) - [i24]Casper Gyurik, Dyon van Vreumingen, Vedran Dunjko:
Structural risk minimization for quantum linear classifiers. CoRR abs/2105.05566 (2021) - [i23]Lieuwe Vinkhuijzen, Tim Coopmans, David Elkouss, Vedran Dunjko, Alfons Laarman:
LIMDD A Decision Diagram for Simulation of Quantum Computing Including Stabilizer States. CoRR abs/2108.00931 (2021) - [i22]Sofiène Jerbi, Lukas J. Fiderer, Hendrik Poulsen Nautrup, Jonas M. Kübler, Hans J. Briegel, Vedran Dunjko:
Quantum machine learning beyond kernel methods. CoRR abs/2110.13162 (2021) - 2020
- [j7]Simon Hangl, Vedran Dunjko, Hans J. Briegel
Skill Learning by Autonomous Robotic Playing Using Active Learning and Exploratory Behavior Composition. Frontiers Robotics AI 7: 42 (2020) - [j6]Walter L. Boyajian, Jens Clausen, Lea M. Trenkwalder
On the convergence of projective-simulation-based reinforcement learning in Markov decision processes. Quantum Mach. Intell. 2(2): 1-21 (2020) - [i21]Casper Gyurik, Chris Cade, Vedran Dunjko:
Towards quantum advantage for topological data analysis. CoRR abs/2005.02607 (2020) - [i20]Mathys Rennela, Alfons Laarman
Hybrid divide-and-conquer approach for tree search algorithms. CoRR abs/2007.07040 (2020)
2010 – 2019
- 2019
- [i19]Yimin Ge, Vedran Dunjko:
A hybrid algorithm framework for small quantum computers with application to finding Hamiltonian cycles. CoRR abs/1907.01258 (2019) - [i18]Jens Clausen, Walter L. Boyajian, Lea M. Trenkwalder, Vedran Dunjko, Hans J. Briegel:
On the convergence of projective-simulation-based reinforcement learning in Markov decision processes. CoRR abs/1910.11914 (2019) - [i17]Sofiène Jerbi, Hendrik Poulsen Nautrup, Lea M. Trenkwalder, Hans J. Briegel, Vedran Dunjko:
A framework for deep energy-based reinforcement learning with quantum speed-up. CoRR abs/1910.12760 (2019) - 2018
- [i16]Vedran Dunjko, Yimin Ge, J. Ignacio Cirac:
Computational speedups using small quantum devices. CoRR abs/1807.08970 (2018) - [i15]Hendrik Poulsen Nautrup, Nicolas Delfosse, Vedran Dunjko, Hans J. Briegel, Nicolai Friis:
Optimizing Quantum Error Correction Codes with Reinforcement Learning. CoRR abs/1812.08451 (2018) - 2017
- [c4]Vedran Dunjko, Jacob M. Taylor, Hans J. Briegel:
Advances in quantum reinforcement learning. SMC 2017: 282-287 - [i14]Alexey A. Melnikov, Hendrik Poulsen Nautrup, Mario Krenn, Vedran Dunjko, Markus Tiersch, Anton Zeilinger, Hans J. Briegel:
Active learning machine learns to create new quantum experiments. CoRR abs/1706.00868 (2017) - [i13]Simon Hangl, Vedran Dunjko, Hans J. Briegel, Justus H. Piater:
Skill Learning by Autonomous Robotic Playing using Active Learning and Creativity. CoRR abs/1706.08560 (2017) - [i12]Theeraphot Sriarunothai, Sabine Wölk, Gouri Shankar Giri, Nicolai Friis
Speeding-up the decision making of a learning agent using an ion trap quantum processor. CoRR abs/1709.01366 (2017) - [i11]Vedran Dunjko, Hans J. Briegel:
Machine learning \& artificial intelligence in the quantum domain. CoRR abs/1709.02779 (2017) - [i10]Vedran Dunjko, Yi-Kai Liu, Xingyao Wu, Jacob M. Taylor:
Super-polynomial separations for quantum-enhanced reinforcement learning. CoRR abs/1710.11160 (2017) - 2016
- [j5]Adi Makmal, Alexey A. Melnikov
Meta-learning within Projective Simulation. IEEE Access 4: 2110-2122 (2016) - [j4]Vedran Dunjko, Theodoros Kapourniotis, Elham Kashefi:
Quantum-enhanced secure delegated classical computing. Quantum Inf. Comput. 16(1&2): 61-86 (2016) - [c3]Jacob M. Taylor, Hans J. Briegel, Vedran Dunjko:
Enhanced learning for agents in quantum-accessible environments. ESANN 2016 - [i9]Adi Makmal, Alexey A. Melnikov, Vedran Dunjko, Hans J. Briegel:
Meta-learning within Projective Simulation. CoRR abs/1602.08017 (2016) - [i8]Vedran Dunjko, Elham Kashefi:
Blind quantum computing with two almost identical states. CoRR abs/1604.01586 (2016) - [i7]Vedran Dunjko, Jacob M. Taylor, Hans J. Briegel:
Quantum-enhanced machine learning. CoRR abs/1610.08251 (2016) - 2015
- [j3]Tomoyuki Morimae, Vedran Dunjko, Elham Kashefi:
Ground state blind quantum computation on AKLT state. Quantum Inf. Comput. 15(3&4): 200-234 (2015) - [i6]Vedran Dunjko, Hans J. Briegel:
Quantum mixing of Markov chains for special distributions. CoRR abs/1502.05511 (2015) - [i5]Vedran Dunjko, Hans J. Briegel:
Sequential quantum mixing for slowly evolving sequences of Markov chains. CoRR abs/1503.01334 (2015) - [i4]Alexey A. Melnikov, Adi Makmal, Vedran Dunjko, Hans J. Briegel:
Projective simulation with generalization. CoRR abs/1504.02247 (2015) - [i3]Vedran Dunjko, Jacob M. Taylor, Hans J. Briegel:
Framework for learning agents in quantum environments. CoRR abs/1507.08482 (2015) - 2014
- [c2]Vedran Dunjko
Composable Security of Delegated Quantum Computation. ASIACRYPT (2) 2014: 406-425 - 2013
- [j2]Vedran Dunjko
Extended phase map decompositions for unitaries. Math. Struct. Comput. Sci. 23(2): 360-385 (2013) - [i2]Vedran Dunjko, Joseph F. Fitzsimons, Christopher Portmann, Renato Renner:
Composable security of delegated quantum computation. CoRR abs/1301.3662 (2013) - 2012
- [j1]Sanja Singer, Sasa Singer, Vedran Novakovic
Novel modifications of parallel Jacobi algorithms. Numer. Algorithms 59(1): 1-27 (2012) - 2010
- [c1]Vedran Dunjko
Algebraic characterisation of one-way patterns. DCM 2010: 85-100 - [i1]Sanja Singer, Sasa Singer, Vedran Novakovic, Aleksandar Uscumlic, Vedran Dunjko:
Novel Modifications of Parallel Jacobi Algorithms. CoRR abs/1008.0201 (2010)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-01 01:12 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: