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)

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)

Near-optimal Quantum algorithms for multivariate mean estimation. - Arjan Cornelissen; Yassine Hamoudi; Sofiène Jerbi (STOC, 2022)

Reinforcement Learning Assisted Recursive QAOA. - Yash J. Patel; Sofiène Jerbi; Thomas Bäck; Vedran Dunjko (CoRR, 2022)

Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning. - Andrea Skolik; Sofiène Jerbi; Vedran Dunjko (Quantum, 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)

Quantum Policy Gradient Algorithms. - Sofiène Jerbi; Arjan Cornelissen; Maris Ozols; Vedran Dunjko (TQC, 2023)

The power and limitations of learning quantum dynamics incoherently. - Sofiène Jerbi; Joe Gibbs; Manuel S. Rudolph; Matthias C. Caro; Patrick J. Coles; Hsin-Yuan Huang; Zoë Holmes (CoRR, 2023)

Shadows of quantum machine learning. - Sofiène Jerbi; Casper Gyurik; Simon C. Marshall; Riccardo Molteni; Vedran Dunjko (CoRR, 2023)

Potential and limitations of random Fourier features for dequantizing quantum machine learning. - Ryan Sweke; Erik Recio; Sofiène Jerbi; Elies Gil-Fuster; Bryce Fuller; Jens Eisert; Johannes Jakob Meyer (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)

An unconditional distribution learning advantage with shallow quantum circuits. - Niklas Pirnay; Sofiène Jerbi; Jean-Pierre Seifert; Jens Eisert (CoRR, 2024)

A quantum-classical reinforcement learning model to play Atari games. - Dominik Freinberger; Julian Lemmel; Radu Grosu; Sofiène Jerbi (CoRR, 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)

Potential and limitations of random Fourier features for dequantizing quantum machine learning. - Ryan Sweke; Erik Recio-Armengol; Sofiène Jerbi; Elies Gil-Fuster; Bryce Fuller; Jens Eisert; Johannes Jakob Meyer (Quantum, 2025)