Vedran Dunjko

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 63

Top Topics

Quantum Computing

Markov Decision Process

Reinforcement Learning

Top Venues

Quantum Mach. Intell.

Publications

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)
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 (2024)
Charles Moussa, Yash J. Patel, Vedran Dunjko, Thomas Bäck, Jan N. van Rijn
Hyperparameter importance and optimization of quantum neural networks across small datasets. Mach. Learn. 113 (4) (2024)
Elies Gil-Fuster, Casper Gyurik, Adrián Pérez-Salinas, Vedran Dunjko
On the relation between trainability and dequantization of variational quantum learning models. CoRR (2024)
Elies Gil-Fuster, Jens Eisert, Vedran Dunjko
On the expressivity of embedding quantum kernels. Mach. Learn. Sci. Technol. 5 (2) (2024)
Simon C. Marshall, Casper Gyurik, Vedran Dunjko
On Bounded Advice Classes. CoRR (2024)
Casper Gyurik, Dyon van Vreumingen, Vedran Dunjko
Structural risk minimization for quantum linear classifiers. Quantum 7 (2023)
Lea M. Trenkwalder, Eleanor Scerri, Thomas E. O'Brien, Vedran Dunjko
Compilation of product-formula Hamiltonian simulation via reinforcement learning. CoRR (2023)
Akash Kundu, Przemyslaw Bedelek, Mateusz Ostaszewski, Onur Danaci, Vedran Dunjko, Jaroslaw Adam Miszczak
Enhancing quantum variational state diagonalization using reinforcement learning techniques. CoRR (2023)
Casper Gyurik, Vedran Dunjko
Exponential separations between classical and quantum learners. CoRR (2023)
Simon C. Marshall, Casper Gyurik, Vedran Dunjko
High Dimensional Quantum Machine Learning With Small Quantum Computers. Quantum 7 (2023)
Waheeda Saib, Xavier Bonet-Monroig, Vedran Dunjko, Ivano Tavernelli, Thomas Bäck, Hao Wang
Benchmarking Adaptive Quantum Circuit Optimization Algorithms for Quantum Chemistry. QCE (2023)
Lieuwe Vinkhuijzen, Tim Coopmans, David Elkouss, Vedran Dunjko, Alfons Laarman
LIMDD: A Decision Diagram for Simulation of Quantum Computing Including Stabilizer States. Quantum 7 (2023)
Alice Barthe, Michele Grossi, Jordi Tura, Vedran Dunjko
Continuous Variables Quantum Algorithm for Solving Ordinary Differential Equations. QCE (2023)
Mathys Rennela, Sebastiaan Brand, Alfons Laarman, Vedran Dunjko
Hybrid divide-and-conquer approach for tree search algorithms. Quantum 7 (2023)
Charles Moussa, Hao Wang, Mauricio Araya-Polo, Thomas Bäck, Vedran Dunjko
Application of quantum-inspired generative models to small molecular datasets. QCE (2023)
Sofiène Jerbi, Arjan Cornelissen, Maris Ozols, Vedran Dunjko
Quantum Policy Gradient Algorithms. TQC (2023)
Charles Moussa, Hao Wang, Mauricio Araya-Polo, Thomas Bäck, Vedran Dunjko
Application of quantum-inspired generative models to small molecular datasets. CoRR (2023)
Sofiène Jerbi, Casper Gyurik, Simon C. Marshall, Riccardo Molteni, Vedran Dunjko
Shadows of quantum machine learning. CoRR (2023)
Elies Gil-Fuster, Jens Eisert, Vedran Dunjko
On the expressivity of embedding quantum kernels. CoRR (2023)
Andrea Skolik, Michele Cattelan, Sheir Yarkoni, Thomas Bäck, Vedran Dunjko
Equivariant quantum circuits for learning on weighted graphs. CoRR (2022)
Casper Gyurik, Vedran Dunjko
On establishing learning separations between classical and quantum machine learning with classical data. CoRR (2022)
Charles Moussa, Jan N. van Rijn, Thomas Bäck, Vedran Dunjko
Hyperparameter Importance of Quantum Neural Networks Across Small Datasets. CoRR (2022)
Casper Gyurik, Chris Cade, Vedran Dunjko
Towards quantum advantage via topological data analysis. Quantum 6 (2022)
Yash J. Patel, Sofiène Jerbi, Thomas Bäck, Vedran Dunjko
Reinforcement Learning Assisted Recursive QAOA. CoRR (2022)
Andrea Skolik, Sofiène Jerbi, Vedran Dunjko
Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning. Quantum 6 (2022)
Simon Marshall, Casper Gyurik, Vedran Dunjko
High Dimensional Quantum Learning With Small Quantum Computers. CoRR (2022)
Charles Moussa, Jan N. van Rijn, Thomas Bäck, Vedran Dunjko
Hyperparameter Importance of Quantum Neural Networks Across Small Datasets. DS (2022)
Sofiène Jerbi, Arjan Cornelissen, Maris Ozols, Vedran Dunjko
Quantum policy gradient algorithms. CoRR (2022)
Sofiène Jerbi, Casper Gyurik, Simon Marshall, Hans J. Briegel, Vedran Dunjko
Variational quantum policies for reinforcement learning. CoRR (2021)
Sofiène Jerbi, Casper Gyurik, Simon Marshall, Hans J. Briegel, Vedran Dunjko
Parametrized Quantum Policies for Reinforcement Learning. NeurIPS (2021)
Mateusz Ostaszewski, Lea M. Trenkwalder, Wojciech Masarczyk, Eleanor Scerri, Vedran Dunjko
Reinforcement learning for optimization of variational quantum circuit architectures. NeurIPS (2021)
Sofiène Jerbi, Lukas J. Fiderer, Hendrik Poulsen Nautrup, Jonas M. Kübler, Hans J. Briegel, Vedran Dunjko
Quantum machine learning beyond kernel methods. CoRR (2021)
Saad Yalouz, Bruno Senjean, Filippo Miatto, Vedran Dunjko
Encoding strongly-correlated many-boson wavefunctions on a photonic quantum computer: application to the attractive Bose-Hubbard model. Quantum 5 (2021)
Davide Orsucci, Vedran Dunjko
On solving classes of positive-definite quantum linear systems with quadratically improved runtime in the condition number. Quantum 5 (2021)
Mateusz Ostaszewski, Lea M. Trenkwalder, Wojciech Masarczyk, Eleanor Scerri, Vedran Dunjko
Reinforcement learning for optimization of variational quantum circuit architectures. CoRR (2021)
Lieuwe Vinkhuijzen, Tim Coopmans, David Elkouss, Vedran Dunjko, Alfons Laarman
LIMDD A Decision Diagram for Simulation of Quantum Computing Including Stabilizer States. CoRR (2021)
Arne Hamann, Vedran Dunjko, Sabine Wölk
Quantum-accessible reinforcement learning beyond strictly epochal environments. Quantum Mach. Intell. 3 (2) (2021)
Valeria Saggio, Beate E. Asenbeck, Arne Hamann, Teodor Strömberg, Peter Schiansky, Vedran Dunjko, Nicolai Friis, Nicholas C. Harris, Michael Hochberg, Dirk R. Englund, Sabine Wölk, Hans J. Briegel, Philip Walther
Experimental quantum speed-up in reinforcement learning agents. Nat. 591 (7849) (2021)
Zhikuan Zhao, Jack K. Fitzsimons, Patrick Rebentrost, Vedran Dunjko, Joseph F. Fitzsimons
Smooth input preparation for quantum and quantum-inspired machine learning. Quantum Mach. Intell. 3 (1) (2021)
Charles Moussa, Hao Wang, Henri Calandra, Thomas Bäck, Vedran Dunjko
Tabu-Driven Quantum Neighborhood Samplers. EvoCOP (2021)
Casper Gyurik, Dyon van Vreumingen, Vedran Dunjko
Structural risk minimization for quantum linear classifiers. CoRR (2021)
Casper Gyurik, Chris Cade, Vedran Dunjko
Towards quantum advantage for topological data analysis. CoRR (2020)
Simon Hangl, Vedran Dunjko, Hans J. Briegel, Justus H. Piater
Skill Learning by Autonomous Robotic Playing Using Active Learning and Exploratory Behavior Composition. Frontiers Robotics AI 7 (2020)
Mathys Rennela, Alfons Laarman, Vedran Dunjko
Hybrid divide-and-conquer approach for tree search algorithms. CoRR (2020)
Walter L. Boyajian, Jens Clausen, Lea M. Trenkwalder, Vedran Dunjko, Hans J. Briegel
On the convergence of projective-simulation-based reinforcement learning in Markov decision processes. Quantum Mach. Intell. 2 (2) (2020)
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 (2019)
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 (2019)
Yimin Ge, Vedran Dunjko
A hybrid algorithm framework for small quantum computers with application to finding Hamiltonian cycles. CoRR (2019)
Hendrik Poulsen Nautrup, Nicolas Delfosse, Vedran Dunjko, Hans J. Briegel, Nicolai Friis
Optimizing Quantum Error Correction Codes with Reinforcement Learning. CoRR (2018)
Vedran Dunjko, Yimin Ge, J. Ignacio Cirac
Computational speedups using small quantum devices. CoRR (2018)
Simon Hangl, Vedran Dunjko, Hans J. Briegel, Justus H. Piater
Skill Learning by Autonomous Robotic Playing using Active Learning and Creativity. CoRR (2017)
Vedran Dunjko, Yi-Kai Liu, Xingyao Wu, Jacob M. Taylor
Super-polynomial separations for quantum-enhanced reinforcement learning. CoRR (2017)
Theeraphot Sriarunothai, Sabine Wölk, Gouri Shankar Giri, Nicolai Friis, Vedran Dunjko, Hans J. Briegel, Christof Wunderlich
Speeding-up the decision making of a learning agent using an ion trap quantum processor. CoRR (2017)
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 (2017)
Vedran Dunjko, Hans J. Briegel
Machine learning \& artificial intelligence in the quantum domain. CoRR (2017)
Vedran Dunjko, Jacob M. Taylor, Hans J. Briegel
Advances in quantum reinforcement learning. SMC (2017)
Vedran Dunjko, Jacob M. Taylor, Hans J. Briegel
Quantum-enhanced machine learning. CoRR (2016)
Vedran Dunjko, Elham Kashefi
Blind quantum computing with two almost identical states. CoRR (2016)
Adi Makmal, Alexey A. Melnikov, Vedran Dunjko, Hans J. Briegel
Meta-learning within Projective Simulation. CoRR (2016)
Vedran Dunjko, Theodoros Kapourniotis, Elham Kashefi
Quantum-enhanced secure delegated classical computing. Quantum Inf. Comput. 16 (1&2) (2016)
Adi Makmal, Alexey A. Melnikov, Vedran Dunjko, Hans J. Briegel
Meta-learning within Projective Simulation. IEEE Access 4 (2016)
Jacob M. Taylor, Hans J. Briegel, Vedran Dunjko
Enhanced learning for agents in quantum-accessible environments. ESANN (2016)
Vedran Dunjko, Hans J. Briegel
Sequential quantum mixing for slowly evolving sequences of Markov chains. CoRR (2015)
Vedran Dunjko, Hans J. Briegel
Quantum mixing of Markov chains for special distributions. CoRR (2015)
Alexey A. Melnikov, Adi Makmal, Vedran Dunjko, Hans J. Briegel
Projective simulation with generalization. CoRR (2015)
Tomoyuki Morimae, Vedran Dunjko, Elham Kashefi
Ground state blind quantum computation on AKLT state. Quantum Inf. Comput. 15 (3&4) (2015)
Vedran Dunjko, Jacob M. Taylor, Hans J. Briegel
Framework for learning agents in quantum environments. CoRR (2015)
Vedran Dunjko, Joseph F. Fitzsimons, Christopher Portmann, Renato Renner
Composable Security of Delegated Quantum Computation. ASIACRYPT (2) (2014)
Vedran Dunjko, Elham Kashefi
Extended phase map decompositions for unitaries. Math. Struct. Comput. Sci. 23 (2) (2013)
Vedran Dunjko, Joseph F. Fitzsimons, Christopher Portmann, Renato Renner
Composable security of delegated quantum computation CoRR (2013)
Sanja Singer, Sasa Singer, Vedran Novakovic, Aleksandar Uscumlic, Vedran Dunjko
Novel modifications of parallel Jacobi algorithms. Numer. Algorithms 59 (1) (2012)
Vedran Dunjko, Elham Kashefi
Algebraic characterisation of one-way patterns DCM (2010)
Sanja Singer, Sasa Singer, Vedran Novakovic, Aleksandar Uscumlic, Vedran Dunjko
Novel Modifications of Parallel Jacobi Algorithms CoRR (2010)