Sofiene Jerbi, MSc

More Information

• FLD Research Documentation

  Publications 2022

  Contributions to Books / Journals

  Journal Article (Original Paper)

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    Skolik, A.; Jerbi, S.; Dunjko, V. (2022): Quantum agents in the Gym: a variational quantum algorithm for deep Q-learning.
    In: Quantum 6, No. 720. (DOI) (Web link)
    
    

  
  
  

  Lectures 2022

  Presentations at Conferences, Symposia, etc.

  Conference Lecture (Upon Registration)

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    Lecturer(s): Jerbi, S.: Quantum machine learning beyond kernel methods.
    International Conference on Quantum Optics, Obergurgl, 2022-02-25. (Web link)
    
    

  Poster Presentation

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    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. (DOI) (Web link)
    
    

  Proceedings Article (Full Paper)

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    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)

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    Cornelissen, A.; Jerbi, S. (2021): Quantum algorithms for multivariate Monte Carlo estimation. (Web link)
    
    
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    Jerbi, S.; Fiderer, L.; Poulsen Nautrup, H.; Kübler, J.; Briegel, Hans J.; Dunjko, V. (2021): Quantum machine learning beyond kernel methods. (Web link)
    
    
  • 
    Jerbi, S.; Gyurik, C.; Marshall, S.; Briegel, Hans J.; Dunjko, V. (2021): Variational quantum policies for reinforcement learning. (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)
    
    
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    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)
    
    
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    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)
    
    
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    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. (DOI) (Web link)
    
    

  Other Publications

  Electronic Publication (Preprint)

  • 
    Poulsen Nautrup, H.; Metger, T.; Iten, R.; Jerbi, S.; Trenkwalder, L.; Wilming, H.; Briegel, Hans J.; Renner, R. (2020): Operationally meaningful representations of physical systems in neural networks. (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)
    
    
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    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)