Vedran Dunjko

Mach. Learn. Sci. Technol., 2024

Quantum computing and persistence in topological data analysis.

[BibT_eX]

[DOI]

Alexander Schmidhuber

Robbie King

Ryu Hayakawa

CoRR, 2024

Improved separation between quantum and classical computers for sampling and functional tasks.

[BibT_eX]

[DOI]

Scott Aaronson

CoRR, 2024

On the relation between trainability and dequantization of variational quantum learning models.

[BibT_eX]

[DOI]

CoRR, 2024

On Bounded Advice Classes.

[BibT_eX]

[DOI]

CoRR, 2024

Reliable Classifications with Guaranteed Confidence Using the Dempster-Shafer Theory of Evidence.

[BibT_eX]

[DOI]

Marie C. Kempkes

Evert P. L. van Nieuwenburg

Jakob Spiegelberg

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Curriculum reinforcement learning for quantum architecture search under hardware errors.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

LIMDD: A Decision Diagram for Simulation of Quantum Computing Including Stabilizer States.

[BibT_eX]

[DOI]

Quantum, September, 2023

High Dimensional Quantum Machine Learning With Small Quantum Computers.

[BibT_eX]

[DOI]

Quantum, August, 2023

Hybrid divide-and-conquer approach for tree search algorithms.

[BibT_eX]

[DOI]

Quantum, March, 2023

Structural risk minimization for quantum linear classifiers.

[BibT_eX]

[DOI]

Dyon van Vreumingen

Quantum, January, 2023

Compilation of product-formula Hamiltonian simulation via reinforcement learning.

[BibT_eX]

[DOI]

CoRR, 2023

Exponential separations between classical and quantum learners.

[BibT_eX]

[DOI]

CoRR, 2023

Enhancing variational quantum state diagonalization using reinforcement learning techniques.

[BibT_eX]

[DOI]

Jaroslaw Adam Miszczak

CoRR, 2023

Shadows of quantum machine learning.

[BibT_eX]

[DOI]

CoRR, 2023

Quantum Policy Gradient Algorithms.

[BibT_eX]

[DOI]

Proceedings of the 18th Conference on the Theory of Quantum Computation, 2023

Benchmarking Adaptive Quantum Circuit Optimization Algorithms for Quantum Chemistry.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

Application of quantum-inspired generative models to small molecular datasets.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

Continuous Variables Quantum Algorithm for Solving Ordinary Differential Equations.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2023

2022

Towards quantum advantage via topological data analysis.

[BibT_eX]

[DOI]

Chris Cade

Quantum, September, 2022

Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning.

[BibT_eX]

[DOI]

Andrea Skolik

Sofiène Jerbi

Quantum, 2022

On establishing learning separations between classical and quantum machine learning with classical data.

[BibT_eX]

[DOI]

CoRR, 2022

Reinforcement Learning Assisted Recursive QAOA.

[BibT_eX]

[DOI]

CoRR, 2022

Equivariant quantum circuits for learning on weighted graphs.

[BibT_eX]

[DOI]

CoRR, 2022

High Dimensional Quantum Learning With Small Quantum Computers.

[BibT_eX]

[DOI]

CoRR, 2022

Hyperparameter Importance of Quantum Neural Networks Across Small Datasets.

[BibT_eX]

[DOI]

Proceedings of the Discovery Science - 25th International Conference, 2022

2021

Encoding strongly-correlated many-boson wavefunctions on a photonic quantum computer: application to the attractive Bose-Hubbard model.

[BibT_eX]

[DOI]

Quantum, 2021

On solving classes of positive-definite quantum linear systems with quadratically improved runtime in the condition number.

[BibT_eX]

[DOI]

Davide Orsucci

Quantum, 2021

Smooth input preparation for quantum and quantum-inspired machine learning.

[BibT_eX]

[DOI]

Quantum Mach. Intell., 2021

Quantum-accessible reinforcement learning beyond strictly epochal environments.

[BibT_eX]

[DOI]

Arne Hamann

Sabine Wölk

Quantum Mach. Intell., 2021

Experimental quantum speed-up in reinforcement learning agents.

[BibT_eX]

[DOI]

Nat., 2021

Quantum machine learning beyond kernel methods.

[BibT_eX]

[DOI]

Sofiène Jerbi

Lukas J. Fiderer

Jonas M. Kübler

CoRR, 2021

Variational quantum policies for reinforcement learning.

[BibT_eX]

[DOI]

CoRR, 2021

Reinforcement learning for optimization of variational quantum circuit architectures.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Parametrized Quantum Policies for Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Tabu-Driven Quantum Neighborhood Samplers.

[BibT_eX]

[DOI]

Proceedings of the Evolutionary Computation in Combinatorial Optimization, 2021

2020

On the convergence of projective-simulation-based reinforcement learning in Markov decision processes.

[BibT_eX]

[DOI]

Quantum Mach. Intell., 2020

Skill Learning by Autonomous Robotic Playing Using Active Learning and Exploratory Behavior Composition.

[BibT_eX]

[DOI]

Frontiers Robotics AI, 2020

Hybrid divide-and-conquer approach for tree search algorithms.

[BibT_eX]

[DOI]

Mathys Rennela

Alfons Laarman

CoRR, 2020

Towards quantum advantage for topological data analysis.

[BibT_eX]

[DOI]

Chris Cade

CoRR, 2020

2019

A framework for deep energy-based reinforcement learning with quantum speed-up.

[BibT_eX]

[DOI]

Sofiène Jerbi

Lea M. Trenkwalder

CoRR, 2019

A hybrid algorithm framework for small quantum computers with application to finding Hamiltonian cycles.

[BibT_eX]

[DOI]

Yimin Ge

CoRR, 2019

2018

Optimizing Quantum Error Correction Codes with Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2018

Computational speedups using small quantum devices.

[BibT_eX]

[DOI]

Yimin Ge

J. Ignacio Cirac

CoRR, 2018

2017

Super-polynomial separations for quantum-enhanced reinforcement learning.

[BibT_eX]

[DOI]

CoRR, 2017

Machine learning \& artificial intelligence in the quantum domain.

[BibT_eX]

[DOI]

CoRR, 2017

Speeding-up the decision making of a learning agent using an ion trap quantum processor.

[BibT_eX]

[DOI]

Theeraphot Sriarunothai

CoRR, 2017

Active learning machine learns to create new quantum experiments.

[BibT_eX]

[DOI]

Alexey A. Melnikov

CoRR, 2017

Skill Learning by Autonomous Robotic Playing using Active Learning and Creativity.

[BibT_eX]

[DOI]

CoRR, 2017

Advances in quantum reinforcement learning.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Systems, Man, and Cybernetics, 2017

2016

Quantum-enhanced secure delegated classical computing.

[BibT_eX]

[DOI]

Theodoros Kapourniotis

Quantum Inf. Comput., 2016

Quantum-enhanced machine learning.

[BibT_eX]

[DOI]

CoRR, 2016

Blind quantum computing with two almost identical states.

[BibT_eX]

[DOI]

CoRR, 2016

Meta-learning within Projective Simulation.

[BibT_eX]

[DOI]

IEEE Access, 2016

Enhanced learning for agents in quantum-accessible environments.

[BibT_eX]

[DOI]

Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015

Ground state blind quantum computation on AKLT state.

[BibT_eX]

[DOI]

Tomoyuki Morimae

Quantum Inf. Comput., 2015

Projective simulation with generalization.

[BibT_eX]

[DOI]

CoRR, 2015

Framework for learning agents in quantum environments.

[BibT_eX]

[DOI]

CoRR, 2015

Sequential quantum mixing for slowly evolving sequences of Markov chains.

[BibT_eX]

[DOI]

CoRR, 2015

Quantum mixing of Markov chains for special distributions.

[BibT_eX]

[DOI]

CoRR, 2015

2014

Composable Security of Delegated Quantum Computation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Cryptology - ASIACRYPT 2014, 2014

2013

Extended phase map decompositions for unitaries.

[BibT_eX]

[DOI]

Math. Struct. Comput. Sci., 2013

2012

Novel modifications of parallel Jacobi algorithms.

[BibT_eX]

[DOI]

Numer. Algorithms, 2012

2010

Algebraic characterisation of one-way patterns

[BibT_eX]

[DOI]