Collection

QTML 2023: Quantum Techniques in Machine Learning

Submission status
Open
Open for submission from
19 February 2024
Submission deadline
Ongoing
This topical collection will include extended versions of original results on the development of quantum techniques in machine learning presented at the 7th International Conference on Quantum Techniques in Machine Learning, QTML 2023, that was held on 20-24 November 2023 at CERN, Switzerland. The QTML 2023 scientific programme consisted of 86 presentations and 160 posters with 333 attendants plus around 100 people following via the webcast. This call is for all the unpublished results that where presented at the conference either orally or as a poster and that can be further refined in complete papers and rielaborated possibly taking into account the comments from the audience. Each submission will be thoroughly refereed according to the standards of the Journal of Quantum Machine Intelligence. We welcome also submissions of work not presented at the conference. Topics include but are not limited to:

• Quantum algorithms for machine learning tasks

• Quantum state reconstruction from data

• Machine learning for experimental quantum information

• Machine learning for Hamiltonian learning

• Variational quantum algorithms

• Learning and optimization with hybrid quantum-classical methods

• Quantum machine learning applications for industry

• Tensor network methods and quantum-inspired machine learning

• Data encoding and processing in quantum systems

• Quantum software

• Quantum learning theory

Editors

  • Michele Grossi Michele Grossi , 

    Michele Grossi

    European Organization for Nuclear Research (CERN), Geneva, Switzerland

  • Zoë Holmes Zoë Holmes  &

    Zoë Holmes

    Information Sciences, Los Alamos National Laboratory, Los Alamos, NM, USA & Institute of Physics, Ecole Polytechnique Fédéderale de Lausanne (EPFL), Lausanne, Switzerland

  • Alesandra Di Pierro Alesandra Di Pierro

    Alesandra Di Pierro

    University of Verona, Italy

Articles

Articles will be displayed here once they are published.