Physical Implementations for Quantum Communication in Quantum Networks. - Hans J. Briegel; J. Ignacio Cirac; Wolfgang Dür; Steven J. van Enk; H. Jeff Kimble; Hideo Mabuchi; Peter Zoller 001 (QCQC, 1998)

Computational model underlying the one-way quantum computer. - Robert Raussendorf; Hans J. Briegel (Quantum Inf. Comput., 2002)

Local invariants for multi-partite entangled states allowing for a simple entanglement criterion. - Hans Aschauer; John Calsamiglia; Marc Hein; Hans J. Briegel (Quantum Inf. Comput., 2004)

Cluster States. - Hans J. Briegel (Compendium of Quantum Physics, 2009)

Projective simulation applied to the grid-world and the mountain-car problem. - Alexey A. Melnikov 001; Adi Makmal; Hans J. Briegel (Artif. Intell. Res., 2014)

Quantum mixing of Markov chains for special distributions. - Vedran Dunjko; Hans J. Briegel (CoRR, 2015)

Sequential quantum mixing for slowly evolving sequences of Markov chains. - Vedran Dunjko; Hans J. Briegel (CoRR, 2015)

Framework for learning agents in quantum environments. - Vedran Dunjko; Jacob M. Taylor; Hans J. Briegel (CoRR, 2015)

Projective simulation with generalization. - Alexey A. Melnikov 001; Adi Makmal; Vedran Dunjko; Hans J. Briegel (CoRR, 2015)

A Chance for Attributable Agency. - Hans J. Briegel; Thomas Müller 007 (Minds Mach., 2015)

Projective Simulation for Classical Learning Agents: A Comprehensive Investigation. - Julian Mautner; Adi Makmal; Daniel Manzano; Markus Tiersch; Hans J. Briegel (New Gener. Comput., 2015)

Enhanced learning for agents in quantum-accessible environments. - Jacob M. Taylor; Hans J. Briegel; Vedran Dunjko (ESANN, 2016)

Meta-learning within Projective Simulation. - Adi Makmal; Alexey A. Melnikov 001; Vedran Dunjko; Hans J. Briegel (IEEE Access, 2016)

Quantum machine learning with glow for episodic tasks and decision games. - Jens Clausen; Hans J. Briegel (CoRR, 2016)

Quantum-enhanced machine learning. - Vedran Dunjko; Jacob M. Taylor; Hans J. Briegel (CoRR, 2016)

Advances in quantum reinforcement learning. - Vedran Dunjko; Jacob M. Taylor; Hans J. Briegel (SMC, 2017)

Skill Learning by Autonomous Robotic Playing using Active Learning and Creativity. - Simon Hangl; Vedran Dunjko; Hans J. Briegel; Justus H. Piater (CoRR, 2017)

Active learning machine learns to create new quantum experiments. - Alexey A. Melnikov 001; Hendrik Poulsen Nautrup; Mario Krenn; Vedran Dunjko; Markus Tiersch; Anton Zeilinger; Hans J. Briegel (CoRR, 2017)

Speeding-up the decision making of a learning agent using an ion trap quantum processor. - Theeraphot Sriarunothai; Sabine Wölk; Gouri Shankar Giri; Nicolai Friis; Vedran Dunjko; Hans J. Briegel; Christof Wunderlich (CoRR, 2017)

Machine learning & artificial intelligence in the quantum domain. - Vedran Dunjko; Hans J. Briegel (CoRR, 2017)

Benchmarking Projective Simulation in Navigation Problems. - Alexey A. Melnikov 001; Adi Makmal; Hans J. Briegel (IEEE Access, 2018)

Faster quantum mixing for slowly evolving sequences of Markov chains. - Davide Orsucci; Hans J. Briegel; Vedran Dunjko (Quantum, 2018)

Machine learning for long-distance quantum communication. - Julius Wallnöfer; Alexey A. Melnikov 001; Wolfgang Dür; Hans J. Briegel (CoRR, 2019)

Photonic architecture for reinforcement learning. - Fulvio Flamini; Arne Hamann 002; Sofiène Jerbi; Lea M. Trenkwalder; Hendrik Poulsen Nautrup; Hans J. Briegel (CoRR, 2019)

A framework for deep energy-based reinforcement learning with quantum speed-up. - Sofiène Jerbi; Hendrik Poulsen Nautrup; Lea M. Trenkwalder; Hans J. Briegel; Vedran Dunjko (CoRR, 2019)

Optimizing Quantum Error Correction Codes with Reinforcement Learning. - Hendrik Poulsen Nautrup; Nicolas Delfosse; Vedran Dunjko; Hans J. Briegel; Nicolai Friis (Quantum, 2019)

Development of swarm behavior in artificial learning agents that adapt to different foraging environments. - Andrea López-Incera; Katja Ried; Thomas Müller 007; Hans J. Briegel (CoRR, 2020)

Collective defense of honeybee colonies: experimental results and theoretical modeling. - Andrea López-Incera; Morgane Nouvian; Katja Ried; Thomas Müller 007; Hans J. Briegel (CoRR, 2020)

Skill Learning by Autonomous Robotic Playing Using Active Learning and Exploratory Behavior Composition. - Simon Hangl; Vedran Dunjko; Hans J. Briegel; Justus H. Piater (Frontiers Robotics AI, 2020)

On the convergence of projective-simulation-based reinforcement learning in Markov decision processes. - Walter L. Boyajian; Jens Clausen; Lea M. Trenkwalder; Vedran Dunjko; Hans J. Briegel (Quantum Mach. Intell., 2020)

Parametrized Quantum Policies for Reinforcement Learning. - Sofiène Jerbi; Casper Gyurik; Simon C. Marshall; Hans J. Briegel; Vedran Dunjko (NeurIPS, 2021)

Variational quantum policies for reinforcement learning. - Sofiène Jerbi; Casper Gyurik; Simon C. Marshall; Hans J. Briegel; Vedran Dunjko (CoRR, 2021)

Quantum machine learning beyond kernel methods. - Sofiène Jerbi; Lukas J. Fiderer; Hendrik Poulsen Nautrup; Jonas M. Kübler; Hans J. Briegel; Vedran Dunjko (CoRR, 2021)

Experimental quantum speed-up in reinforcement learning agents. - Valeria Saggio; Beate E. Asenbeck; Arne Hamann 002; Teodor Strömberg; Peter Schiansky; Vedran Dunjko; Nicolai Friis; Nicholas C. Harris; Michael Hochberg; Dirk R. Englund; Sabine Wölk; Hans J. Briegel; et al. (Nat., 2021)

Automated Gadget Discovery in Science. - Lea M. Trenkwalder; Andrea López-Incera; Hendrik Poulsen Nautrup; Fulvio Flamini; Hans J. Briegel (CoRR, 2022)

Operationally meaningful representations of physical systems in neural networks. - Hendrik Poulsen Nautrup; Tony Metger; Raban Iten; Sofiène Jerbi; Lea M. Trenkwalder; Henrik Wilming; Hans J. Briegel; Renato Renner (Mach. Learn. Sci. Technol., 2022)

Reinforcement learning and decision making via single-photon quantum walks. - Fulvio Flamini; Marius Krumm; Lukas J. Fiderer; Thomas Müller 007; Hans J. Briegel (CoRR, 2023)

Optimal foraging strategies can be learned and outperform Lévy walks. - Gorka Muñoz-Gil; Andrea López-Incera; Lukas J. Fiderer; Hans J. Briegel (CoRR, 2023)

Variational measurement-based quantum computation for generative modeling. - Arunava Majumder; Marius Krumm; Tina Radkohl; Hendrik Poulsen Nautrup; Sofiène Jerbi; Hans J. Briegel (CoRR, 2023)

Measurement-based quantum computation from Clifford quantum cellular automata. - Hendrik Poulsen Nautrup; Hans J. Briegel (CoRR, 2023)

How a Minimal Learning Agent can Infer the Existence of Unobserved Variables in a Complex Environment. - Benjamin Eva; Katja Ried; Thomas Müller 007; Hans J. Briegel (Minds Mach., 2023)

Automated gadget discovery in the quantum domain. - Lea M. Trenkwalder; Andrea López-Incera; Hendrik Poulsen Nautrup; Fulvio Flamini; Hans J. Briegel (Mach. Learn. Sci. Technol., 2023)

The Min-Entropy of Classical-Quantum Combs for Measurement-Based Applications. - Isaac D. Smith; Marius Krumm; Lukas J. Fiderer; Hendrik Poulsen Nautrup; Hans J. Briegel (Quantum, 2023)

Multi-Excitation Projective Simulation with a Many-Body Physics Inspired Inductive Bias. - Philip A. LeMaitre; Marius Krumm; Hans J. Briegel (CoRR, 2024)

A Universal Quantum Computer From Relativistic Motion. - Philip A. LeMaitre; T. Rick Perche; Marius Krumm; Hans J. Briegel (CoRR, 2024)

Free Energy Projective Simulation (FEPS): Active inference with interpretability. - Joséphine Pazem; Marius Krumm; Alexander Q. Vining; Lukas J. Fiderer; Hans J. Briegel (CoRR, 2024)

Quantum circuit synthesis with diffusion models. - Florian Fürrutter; Gorka Muñoz-Gil; Hans J. Briegel (Nat. Mac. Intell., 2024)

Hybrid discrete-continuous compilation of trapped-ion quantum circuits with deep reinforcement learning. - Francesco Preti; Michael Schilling 004; Sofiène Jerbi; Lea M. Trenkwalder; Hendrik Poulsen Nautrup; Felix Motzoi; Hans J. Briegel (Quantum, 2024)

Learning to reset in target search problems. - Gorka Muñoz-Gil; Hans J. Briegel; Michele Caraglio (CoRR, 2025)

The Work Capacity of Channels with Memory: Maximum Extractable Work in Percept-Action Loops. - Lukas J. Fiderer; Paul C. Barth; Isaac D. Smith; Hans J. Briegel (CoRR, 2025)

Synthesis of discrete-continuous quantum circuits with multimodal diffusion models. - Florian Fürrutter; Zohim Chandani; Ikko Hamamura; Hans J. Briegel; Gorka Muñoz-Gil (CoRR, 2025)

Interpretable representation learning of quantum data enabled by probabilistic variational autoencoders. - Paulin de Schoulepnikoff; Gorka Muñoz-Gil; Hendrik Poulsen Nautrup; Hans J. Briegel (CoRR, 2025)