Sofiene Jerbi, MSc
PhD Student
Room:
4S13 ITP
Phone: +43 512 507
52245
Email:
Sofiene.Jerbi[at]uibk.ac.at
Research group: Quantum Information and Computation
More Information
-
Publications 2022
Contributions to Books / Journals
Journal Article (Original Paper)
-
Poulsen Nautrup, H.; Metger, T.; Iten, R.; Jerbi, S.; Trenkwalder, L.; Wilming, H.; Briegel, Hans J.; Renner, R. (2022): Operationally meaningful representations of physical systems in neural networks.
In: Machine Learning: Science and Technology 3/4, Nr. 045025. (DOI) (Web link) -
Skolik, A.; Jerbi, S.; Dunjko, V. (2022): Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning.
In: Quantum. The Open Journal for Quantum Science 6, No. 720. (DOI) (Web link)
Proceedings Article (Full Paper)
-
Cornelissen, A.; Hamoudi, Y.; Jerbi, S. (2022): Near-optimal quantum algorithms for multivariate mean estimation.
In: Leonardi, S.; Gupta, A.: STOC 2022: Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing. New York: Association for Computing Machinery., ISBN 978-1-4503-9264-8, pp. 33 - 43. (DOI) (Web link)
Other Publications
Electronic Publication (Preprint)
-
Jerbi, S.; Cornelissen, A.; Ozols, M.; Djunko, V (2022): Quantum policy gradient algorithms. (Web link)
-
Patel, Y. J.; Jerbi, S.; Bäck, T.; Dunjko, V. (2022): Reinforcement learning assisted recursive QAOA. (Web link)
Lectures 2022
Presentations at Conferences, Symposia, etc.
Conference Lecture (Upon Registration)
-
Lecturer(s): Jerbi, S.: Unifying quantum machine learning models: theory and practical implications.
Quantum Techniques in Machine Learning - QTML 2022, Neapel, 2022-11-11. (Web link) -
Lecturer(s): Jerbi, S.: Quantum machine learning beyond kernel methods.
International Conference on Quantum Optics, Obergurgl, 2022-02-25. (Web link)
Poster Presentation
-
Lecturer(s): Jerbi, S.: Unifying quantum machine learning models: theory and practical implications.
DK-ALM Summer School 2022, Lech, 2022-09-14. (Web link) -
Lecturer(s): Jerbi, S.: Unifying quantum machine learning models: theory and practical implications.
SFB BeyondC Conference 2022 - Frontiers of Quantum Information Science, Wien, 2022-09-05. (Web link) -
Lecturer(s): Jerbi, S.: Unifying quantum machine learning models: theory and practical implications.
Measurement-Based Quantum Computation, Learning and Agency (MBQC 2022), Obergurgl, 2022-09-01. (Web link) -
Lecturer(s): Jerbi, S.: Variational quantum circuits for reinforcement learning.
International Conference on Quantum Optics, Obergurgl, 2022-02-22. (Web link)
Publications 2021
Contributions to Books / Journals
Journal Article (Original Paper)
-
Jerbi, S.; Trenkwalder, Lea; Poulsen Nautrup, H.; Briegel, Hans J.; Dunjko, Vedran (2021): Quantum Enhancements for Deep Reinforcement Learning in Large Spaces.
In: PRX Quantum 2/1, No. 010328. (Full-text) (DOI) (Web link)
Proceedings Article (Full Paper)
-
Jerbi, S.; Gyurik, C.; Marshall, S. C.; Briegel, Hans J.; Dunjko, V. (2021): Parametrized quantum policies for reinforcement learning.
In: Ranzato, M.; Beygelzimer, A.; LIang, P.S.; Vaughan, J.W.; Dauphin, Y.: 35th Conference on Neural Information Processing Systems. Advances in Neural Information Processing Systems 34 pre-proceedings (NeurIPS 2021). Monday December 6 through Tuesday December 14, 2021. Virtual-only Conference. San Diego: Neural Information Processing Systems Foundation., online. (Web link)
Other Publications
Electronic Publication (Preprint)
-
Cornelissen, A.; Jerbi, S. (2021): Quantum algorithms for multivariate Monte Carlo estimation. (DOI) (Web link)
-
Jerbi, S.; Fiderer, L.; Poulsen Nautrup, H.; Kübler, J.; Briegel, Hans J.; Dunjko, V. (2021): Quantum machine learning beyond kernel methods. (DOI) (Web link)
Lectures 2021
Presentations at Conferences, Symposia, etc.
Conference Lecture (Upon Registration)
-
Lecturer(s): Jerbi, S.: Parametrized quantum circuits for reinforcement learning.
Quantum Techniques for Machine Learning (QTML) 2021, Tokyo, online, 2021-11-10. (Web link) -
Lecturer(s): Jerbi, S.: Variational quantum policies for reinforcement learning.
Gemeinsame Jahrestagung der SPS und ÖPG 2021 (Swiss and Austrian Physical Societies), Innsbruck, 2021-09-02. (Web link)
Lecture at Summer-/Winterschool
-
Lecturer(s): Jerbi, S.: Quantum-enhanced reinforcement learning.
Summer School: Machine Learning in Quantum Physics and Chemistry 2021, Warschau, 2021-08-31. (Web link) -
Lecturer(s): Jerbi, S.: Variational quantum policies for reinforcement learning.
IMPRS-MPHQ-BeyondC online Summer School 2021, Wien, online, 2021-07-15. (Web link)
Poster Presentation
-
Lecturer(s): Jerbi, S.: Parametrized quantum policies for reinforcement learning.
Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), San Diego, 2021-12-08. (Web link) -
Lecturer(s): Jerbi, S.: Variational quantum algorithms for reinforcement learning.
DK-Alm Summer School, Pertisau, 2021-07-14. (Web link)
Publications 2020
Contributions to Books / Journals
Journal Article (Original Paper)
-
Flamini, Fulvio; Hamann, Arne; Jerbi, S.; Trenkwalder, Lea; Poulsen Nautrup, H.; Briegel, Hans J. (2020): Photonic architecture for reinforcement learning.
In: New Journal of Physics 22, No. 045002. (Full-text) (DOI) (Web link)
Lectures 2020
Presentations at Conferences, Symposia, etc.
Conference Lecture (Invited Lecture)
-
Lecturer(s): Flamini, Fulvio Co-author(s): Hamann, A.; Jerbi, S.; Trenkwalder, L.; Poulsen Nautrup, H.; Briegel, Hans J.: Photonic architecture for reinforcement learning.
22nd Photonics North Conference, Québec, 2020-05-26. (Web link)
Conference Lecture (Upon Registration)
-
Lecturer(s): Jerbi, S: Quantum enhancements for deep reinforcement learning in large spaces.
Quantum Techniques in Machine Learning / QTML 2020, Cambridge, Massachusetts, 2020-11-12. (Web link)
Lectures 2019
Presentations at Conferences, Symposia, etc.
Conference Lecture (Invited Lecture)
-
Lecturer(s): Flamini, Fulvio Co-author(s): Hamann, A.; Jerbi, S.; Trenkwalder, L.; Poulsen Nautrup, H.; Briegel, Hans J.: Photonic architecture for reinforcement learning.
1. DPG Herbsttagung 2019 on Quantum Science and Information Technologies, Freiburg, 2019-09-23. (Web link) -
Lecturer(s): Jerbi, S. Co-author(s): Poulsen Nautrup, Hendrik; Trenkwalder, Lea; Briegel, Hans J.; Vedran, Dunjko: A framework for deep energy-based reinforcement learning with quantum speed-up.
1. DPG Herbsttagung 2019 on Quantum Science and Information Technologies, Freiburg, 2019-09-23. (Web link)
Poster Presentation
-
Lecturer(s): Flamini, Fulvio Co-author(s): Hamann, A.; Jerbi, S.; Trenkwalder, L. M.; Poulsen Nautrup, H; Briegel, Hans J.: Photonic architecture for reinforcement learning.
Austrian Quantum Information Conference 2019, Wien, 2019-10-31. (Web link) -
Lecturer(s): Flamini, Fulvio Co-author(s): Hamann, A.; Jerbi, S.; Trenkwalder, L.; Poulsen Nautrup, H.; Briegel, Hans J.: Photonic architecture for reinforcement learning.
Vienna Graduate Conference on Complex Quantum Systems, Wien, 2019-10-28. (Web link) -
Lecturer(s): Jerbi, S. Co-author(s): Poulsen Nautrup, H.; Trenkwalder, L.; Briegel, Hans J.; Dunjko, V.: A framework for deep energy-based reinforcement learning with quantum speed-up.
Quantum Techniques in Machine Learning (QTML2019), Daejeon, 2019-10-22. (Web link) -
Lecturer(s): Jerbi, S. Co-author(s): Poulsen Nautrup, H.; Trenkwalder, L.M.; Briegel, Hans J.; Dunjko, V.: A framework for deep energy-based reinforcement learning with quantum speed-up.
Austrian Quantum Information Conference 2019, Wien, 2019-10-31. (Web link)
-