Remmy Zen

Publication

Reinforcement Learning for Quantum Computing Project

Collaborators: Jan Olle, Matteo Puviani, Sangkha Borah, Maximilian Nägele, Olev Yevtushenko, Luis Colmenarez, Markus Müller, Florian Marquardt

Grant: Munich Quantum Valley

  • M. Nägele, J. Olle, T. Fösel, Remmy Zen, F. Marquardt. Tackling Decision Processes with Non-Cumulative Objectives using Reinforcement Learning. arXiv:2405.13609 (2024). [Link]
  • Remmy Zen, J. Olle, L. Colmenarez, M. Puviani, M. Müller, F. Marquardt. Quantum Circuit Discovery for Fault-Tolerant Logical State Preparation with Reinforcement Learning. arXiv:2402.17761 (2024). [Link]
  • M. Puviani, S. Borah, Remmy Zen, J. Olle, F. Marquardt. Boosting the Gottesman-Kitaev-Preskill quantum error correction with non-Markovian feedback. arXiv:2312.07391 (2023). [Link]
  • J. Olle, Remmy Zen, M. Puviani, F. Marquardt. Simultaneous Discovery of Quantum Error Correction Codes and Encoders with a Noise-Aware Reinforcement Learning Agent. arXiv:2311.04750 (2023). [Link]

Neural-Network Quantum States Project

Collaborators: Christian Miniatura (Majulab/CQT), Dario Poletti (SUTD), Frederic Hebert (INPHYNI Nice), Mario Gattobigio (INPHYNI Nice)

Grant: Deep Quantum: AI for and from Quantum Physics (PHC Merlion Grant Institut Français de Singapour)

  • Z Wu, Remmy Zen, HP Casagrande, S Bressan, D Poletti. Supervised Training of Neural-Network Quantum States for the Next Nearest Neighbor Ising model. arXiv:2305.03394 (2023). [Link]
  • Remmy Zen, S. Bressan. (2021). Transfer Learning for Larger, Broader, and Deeper Neural-Network Quantum States. In Proceedings from the 32nd Database and Expert Systems Applications, pp 207-219. [Link]
  • Remmy Zen, L. My, R. Tan, F. Hebert, M. Gattobigio, C. Miniatura, D. Poletti, S. Bressan. (2020). Finding Quantum Critical Points with Neural-Network Quantum States. In Proceedings from the 24th European Conference on Artificial Intelligence. Santiago De Compostela, Spain. [Extended Version]
  • Remmy Zen, L. My, R. Tan, F. Hebert, M. Gattobigio, C. Miniatura, D. Poletti, S. Bressan. (2019). Transfer learning for scalability of neural-network quantum states. Phys. Rev. E, vol. 101, p. 053 301, 5 May 2020. [preprint] [paper]

Other Past Projects

Collaborators: Abhishek Saha (TU Delft), Dewa M.S. Arsa (Udayana Univ.), Ismail Khalil (JKU Linz), Laure Sione (Imperial College London), Ngurah Agus Sanjaya (Udayana Univ.)

Grant: Water Challenge Analytics (NUS IDS)

  • R. Zhang, Remmy Zen, A. Saha, S. Bressan. (2020). Hydrological Process Surrogate Modelling and Simulation with Neural Networks. In Proceedings from the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD). Singapore, Singapore. [paper]
  • J. Xing, R. Zhang, Remmy Zen, D. M. S. Arsa, I. Khalil, S. Bressan. (2019). Building Extraction from Google Earth Images. In Proceedings from The 21st International Conference on Information Integration and Web-based Applications & Services (iiWAS2019). Munich, Germany.
  • J. Xing, R. Zhang, Remmy Zen, N. A. Sanjaya, L. Sione, I. Khalil, S. Bressan. (2019). Microbiological Water Quality Test Results Extraction from Mobile Photographs. In Proceedings from The 21st International Conference on Information Integration and Web-based Applications & Services (iiWAS2019). Munich, Germany.
  • Remmy Zen, D.M.S. Arsa, R. Zhang, N.A. Sanjaya, S. Bressan. (2019). Rainfall Estimation from Traffic Cameras. In Proceedings from The 30th International Conference on Database and Expert Systems Applications (DEXA). Linz, Austria. [Link].

Collaborator: Ashish Dandekar (Lecturer at NUS)

  • A. Dandekar, Remmy Zen, S. Bressan. (2018). A Comparative Study of Synthetic Dataset Generation Techniques. In Proceedings from The 29th International Conference on Database and Expert Systems Applications (DEXA). Regensburg, Germany. [Link]. [Technical Report]
  • A. Dandekar, Remmy Zen, S. Bressan. (2017). Comparative Evaluation of Synthetic Data Generation Methods. In Deep Learning Security Workshop (DLSW) 2017. Singapore.
  • A. Dandekar, Remmy Zen, S. Bressan. (2017). Generating Fake But Realistic Headlines Using Deep Neural Networks. In Proceedings from The 28th International Conference on Database and Expert Systems Applications (DEXA). pp. 427-440. Lyon, France. [Link]