Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications - Francesco Cremonesi; Marc Vesin; Sergen Cansiz; Yannick Bouillard; Irene Balelli; Lucia Innocenti; Santiago Silva; Samy-Safwan Ayed; Riccardo Taiello; Laetitia Kameni; Richard Vidal; Fanny Orlhac; et al. (CoRR, 2023)

FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings - Jean Ogier du Terrail; Samy-Safwan Ayed; Edwige Cyffers; Felix Grimberg; Chaoyang He; Regis Loeb; Paul Mangold; Tanguy Marchand; Othmane Marfoq; Erum Mushtaq; Boris Muzellec; Constantin Philippenko; et al. (Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022)

FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings - Jean Ogier du Terrail; Samy-Safwan Ayed; Edwige Cyffers; Felix Grimberg; Chaoyang He; Regis Loeb; Paul Mangold; Tanguy Marchand; Othmane Marfoq; Erum Mushtaq; Boris Muzellec; Constantin Philippenko; et al. (CoRR, 2022)