Lea Trenkwalder,

More Information

• FLD Research Documentation

  Publications 2023

  Contributions to Books / Journals

  Journal Article (Original Paper)

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    Trenkwalder, L.; Lopez-Incera, A.; Poulsen Nautrup, H.; Flamini, F.; Briegel, Hans J. (2023): Automated gadget discovery in the quantum domain.
    In: Machine Learning: Science and Technology 4/3, No. 035043. (DOI) (Web link)
    
    

  Other Publications

  Electronic Publication (Preprint)

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    Trenkwalder, L.; Scerri, E.; O'Brien, T. E.; Dunjko, V. (2023): Compilation of product-formula Hamiltonian simulation via reinforcement learning. (Web link)
    
    

  
  
  

  Lectures 2023

  Presentations at Conferences, Symposia, etc.

  Lecture at Project Meeting / Research Cooperation Meeting

  • 
    Lecturer(s): Trenkwalder, L.; Poulsen Nautrup, H.: Learning from reinforcement learning.
    Workshop "Innsbruck-Konstanz meeting on physics and philosophy", Bregenz, 2023-09-18.
    
    

  
  
  

  Publications 2022

  Contributions to Books / Journals

  Journal Article (Original Paper)

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    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)
    
    

  
  
  

  Publications 2021

  Contributions to Books / Journals

  Journal Article (Original Paper)

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    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)

  • 
    Ostaszewski, M.; Trenkwalder, Lea; Masarczyk, W.; Scerri, E.; Dunjko, V. (2021): Reinforcement learning for optimization of variational quantum circuit architectures.
    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)
    
    

  
  
  

  Publications 2020

  Contributions to Books / Journals

  Journal Article (Original Paper)

  • 
    Boyajian, Walter L.; Clausen, J.; Trenkwalder, L.; Dunjko, V.; Briegel, Hans J. (2020): On the convergence of projective-simulation-based reinforcement learning in Markov decision processes.
    In: Quantum Machine Intelligence 2/2, No. 13. (Full-text) (DOI) (Web link)
    
    
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    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)
    
    

  
  
  

  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)
    
    
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    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)
    
    
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    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)
    
    
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    Lecturer(s): Trenkwalder, L. Co-author(s): Clausen, J.; Boyajian, W.; Dunjko, V.; Briegel, Hans J.: Convergence proof for an agent-based reinforcement learning approach in Markov decision processes.
    1. DPG Herbsttagung 2019 on Quantum Science and Information Technologies, Freiburg, 2019-09-25. (Web link)
    
    

  
  
  

  Lectures 2018

  Presentations at Conferences, Symposia, etc.

  Conference Lecture (Upon Registration)

  • 
    Lecturer(s): Trenkwalder, Lea: Projective simulation applied to non-Markovian problems.
    82. Jahrestagung der DPG und DPG-Frühjahrstagung, Erlangen, 2018-03-05. (Web link)