Flower: A Friendly Federated Learning Research Framework. - Daniel J. Beutel; Taner Topal; Akhil Mathur; Xinchi Qiu; Titouan Parcollet; Nicholas D. Lane (CoRR, 2020)

A first look into the carbon footprint of federated learning. - Xinchi Qiu; Titouan Parcollet; Daniel J. Beutel; Taner Topal; Akhil Mathur; Nicholas D. Lane (CoRR, 2020)

Secure aggregation for federated learning in flower. - Kwing Hei Li; Pedro Porto Buarque de Gusmão; Daniel J. Beutel; Nicholas D. Lane (DistributedML@CoNEXT, 2021)

A first look into the carbon footprint of federated learning. - Xinchi Qiu; Titouan Parcollet; Javier Fernández-Marqués; Pedro Porto Buarque de Gusmão; Daniel J. Beutel; Taner Topal; Akhil Mathur; Nicholas D. Lane (CoRR, 2021)

On-device Federated Learning with Flower. - Akhil Mathur; Daniel J. Beutel; Pedro Porto Buarque de Gusmão; Javier Fernández-Marqués; Taner Topal; Xinchi Qiu; Titouan Parcollet; Yan Gao 016; Nicholas D. Lane (CoRR, 2021)

End-to-End Speech Recognition from Federated Acoustic Models. - Yan Gao 016; Titouan Parcollet; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Daniel J. Beutel; Nicholas D. Lane (CoRR, 2021)

MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation. - Alexandros Karargyris; Renato Umeton; Micah J. Sheller; Alejandro Aristizabal; Johnu George; Srini Bala; Daniel J. Beutel; Victor Bittorf; Akshay Chaudhari; Alexander Chowdhury; Cody Coleman; Bala Desinghu; et al. (CoRR, 2021)

End-to-End Speech Recognition from Federated Acoustic Models. - Yan Gao 016; Titouan Parcollet; Salah Zaiem; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Daniel J. Beutel; Nicholas D. Lane (ICASSP, 2022)

Gradient-less Federated Gradient Boosting Tree with Learnable Learning Rates. - Chenyang Ma; Xinchi Qiu; Daniel J. Beutel; Nicholas D. Lane (EuroMLSys@EuroSys, 2023)

Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates. - Chenyang Ma; Xinchi Qiu; Daniel J. Beutel; Nicholas D. Lane (CoRR, 2023)

A First Look into the Carbon Footprint of Federated Learning. - Xinchi Qiu; Titouan Parcollet; Javier Fernández-Marqués; Pedro P. B. de Gusmao; Yan Gao 016; Daniel J. Beutel; Taner Topal; Akhil Mathur; Nicholas D. Lane (J. Mach. Learn. Res., 2023)

Federated benchmarking of medical artificial intelligence with MedPerf. - Alexandros Karargyris; Renato Umeton; Micah J. Sheller; Alejandro Aristizabal; Johnu George; Anna Wuest; Sarthak Pati; Hasan Kassem; Maximilian Zenk; Ujjwal Baid; Prakash Narayana Moorthy; Alexander Chowdhury; et al. (Nat. Mac. Intell., 2023)

Federated Learning for IoT. - Daniel J. Beutel (FMEC, 2024)

Keynote Speech 4 Federated Learning for IoT. - Daniel J. Beutel (IOTSMS, 2024)

Supercharging Federated Learning with Flower and NVIDIA FLARE. - Holger R. Roth; Daniel J. Beutel; Yan Cheng; Javier Fernández-Marqués; Heng Pan; Chester Chen; Zhihong Zhang 001; Yuhong Wen; Sean Yang; Isaac Yang; Yuan-Ting Hsieh; Ziyue Xu 001; et al. (CoRR, 2024)

FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models. - Yan Gao 016; Massimo Roberto Scamarcia; Javier Fernández-Marqués; Mohammad Naseri; Chong Shen Ng; Dimitris Stripelis; Zexi Li; Tao Shen; Jiamu Bai; Daoyuan Chen; Zikai Zhang; Rui Hu; et al. (CoRR, 2025)