Harnessing Photon Indistinguishability in Quantum Extreme Learning Machines
This study investigates Quantum Extreme Learning Machines (QELMs), which enhance classical Extreme Learning Machines (ELMs) by incorporating quantum features.
Authors
- Hugo Defienne (ORCID: https://orcid.org/0000-0002-5543-2885)
- Steffen Wilksen (ORCID: https://orcid.org/0000-0002-8556-2277)
- Adrian Makowski (ORCID: https://orcid.org/0000-0002-5531-0060)
- Edoardo Charbon (ORCID: https://orcid.org/0000-0002-0620-3365)
- Sylvain Gigan (ORCID: https://orcid.org/0000-0002-9914-6231)
- Christopher Gies (ORCID: https://orcid.org/0000-0002-5713-7089)
- Malo Joly
- Lukas Porstendorfer
Institutions
- Centre National de la Recherche Scientifique (FR)
- University of Bremen (DE)
- Laboratoire Kastler Brossel (FR)
- École Normale Supérieure - PSL (FR)
- Sorbonne Université (FR)
- Institut des NanoSciences de Paris (FR)
- École Polytechnique Fédérale de Lausanne (CH)
Publication Details
- Published
- 2025-06-23
- DOI
- https://doi.org/10.1109/cleo/europe-eqec65582.2025.11111587
- Primary Topic
- Machine Learning and ELM
- Type
- article
- Field-Weighted Citation Impact
- 0.00