A generic framework for privacy preserving deep learning. - Théo Ryffel; Andrew Trask; Morten Dahl; Bobby Wagner; Jason Mancuso; Daniel Rueckert; Jonathan Passerat-Palmbach (CoRR, 2018)

Partially Encrypted Deep Learning using Functional Encryption. - Théo Ryffel; David Pointcheval; Francis R. Bach; Edouard Dufour-Sans; Romain Gay (NeurIPS, 2019)

Partially Encrypted Machine Learning using Functional Encryption. - Théo Ryffel; Edouard Dufour Sans; Romain Gay; Francis R. Bach; David Pointcheval (CoRR, 2019)

Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. - Miles Brundage; Shahar Avin; Jasmine Wang; Haydn Belfield; Gretchen Krueger; Gillian K. Hadfield; Heidy Khlaaf; Jingying Yang; Helen Toner; Ruth Fong; Tegan Maharaj; Pang Wei Koh; et al. (CoRR, 2020)

ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing. - Théo Ryffel; David Pointcheval; Francis R. Bach (CoRR, 2020)

Privacy-preserving medical image analysis. - Alexander Ziller; Jonathan Passerat-Palmbach; Théo Ryffel; Dmitrii Usynin; Andrew Trask; Ionésio Da Lima Costa Junior; Jason Mancuso; Marcus R. Makowski; Daniel Rueckert; Rickmer Braren; Georgios Kaissis (CoRR, 2020)

Syft 0.5: A Platform for Universally Deployable Structured Transparency. - Adam James Hall; Madhava Jay; Tudor Cebere; Bogdan Cebere; Koen Lennart van der Veen; George Muraru; Tongye Xu; Patrick Cason; William Abramson; Ayoub Benaissa; Chinmay Shah; Alan Aboudib; et al. (CoRR, 2021)

End-to-end privacy preserving deep learning on multi-institutional medical imaging. - Georgios Kaissis; Alexander Ziller; Jonathan Passerat-Palmbach; Théo Ryffel; Dmitrii Usynin; Andrew Trask; Ionésio Lima; Jason Mancuso; Friederike Jungmann; Marc-Matthias Steinborn; Andreas Saleh; Marcus R. Makowski; et al. (Nat. Mach. Intell., 2021)

Differential Privacy Guarantees for Stochastic Gradient Langevin Dynamics. - Théo Ryffel; Francis R. Bach; David Pointcheval (CoRR, 2022)

AriaNN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing. - Théo Ryffel; Pierre Tholoniat; David Pointcheval; Francis R. Bach (Proc. Priv. Enhancing Technol., 2022)

Cryptography for Privacy-Preserving Machine Learning. (Cryptographie pour l'apprentissage automatique respectueux de la vie privée). - Théo Ryffel (2022)

Large Language Models as Instructors: A Study on Multilingual Clinical Entity Extraction. - Simon Meoni; Éric de la Clergerie; Théo Ryffel (BioNLP@ACL, 2023)

Annotate French Clinical Data Using Large Language Model Predictions. - Simon Meoni; Théo Ryffel; Éric de la Clergerie (ICHI, 2023)

Annotation d'entités cliniques en utilisant les Larges Modèles de Langue. - Simon Meoni; Théo Ryffel; Éric Villemonte de la Clergerie (CORIA-TALN (1), 2023)