28 citations
- Centre National de la Recherche ScientifiqueFR4 papers
- Aix-Marseille UniversitéFR3 papers
- Université Côte d'AzurFR3 papers
- Université Grenoble AlpesFR3 papers
- Centre de physique des particules de MarseilleFR2 papers
- Institut de Biologie ValroseFR2 papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR2 papers
- Institut polytechnique de GrenobleFR2 papers
- Observatoire de la Côte d’AzurFR2 papers
- Centre de Recherche sur l'Hétéro-Epitaxie et ses ApplicationsFR1 paper
- Centre Inria d'Université Côte d'AzurFR1 paper
- Centre National d'Études SpatialesFR1 paper
5 papers · 1 filter
Validation of a new 60 MeV proton beam-line for radiation hardness testing
Petter Hofverberg, Francoise Bezerra, Marine Ruffenach +4
A 60 MeV proton beam-line has been developed in Nice, France, in collaboration with the Centre National d'Etudes Spatiales (CNES). Experimental results are presented here to valida…
Radiation Tolerance of Low-Noise Photoreceivers for the LISA Space Mission
P. Colcombet, N. Dinu-Jaeger, C. Inguimbert +16
This study investigates the effects of space environmental radiation on the performance of InGaAs Quadrant Photodiodes (QPDs) and assesses their suitability for the Laser Interfero…
A high sensitivity Cherenkov detector for Prompt Gamma Timing and Time Imaging
Maxime Jacquet, Saba Ansari, Marie-Laure Gallin-Martel +13
We recently proposed a new approach for the real-time monitoring of particle therapy treatments with the goal of achieving high sensitivities on the particle range measurement alre…
Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications
Francesco Cremonesi, Marc Vesin, Sergen Cansiz +16
The real-world implementation of federated learning is complex and requires research and development actions at the crossroad between different domains ranging from data science, t…
Are labels informative in semi-supervised learning? -- Estimating and leveraging the missing-data mechanism
Aude Sportisse, Hugo Schmutz, Olivier Humbert +2
Semi-supervised learning is a powerful technique for leveraging unlabeled data to improve machine learning models, but it can be affected by the presence of ``informative'' labels,…