Théo Ryffel

According to our database, Théo Ryffel authored at least 14 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Annotation d'entités cliniques en utilisant les Larges Modèles de Langue.

Simon Meoni, Théo Ryffel, Éric Villemonte de la Clergerie

Proceedings of the Actes de CORIA-TALN 2023. Actes de la 30e Conférence sur le Traitement Automatique des Langues Naturelles, TALN 2023 - Volume 1 : travaux de recherche originaux, 2023

Annotate French Clinical Data Using Large Language Model Predictions.

Simon Meoni, Théo Ryffel, Éric de la Clergerie

Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

Large Language Models as Instructors: A Study on Multilingual Clinical Entity Extraction.

Simon Meoni, Éric de la Clergerie, Théo Ryffel

Proceedings of the 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, 2023

2022

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

Théo Ryffel

PhD thesis, 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

Differential Privacy Guarantees for Stochastic Gradient Langevin Dynamics.

Théo Ryffel, Francis R. Bach, David Pointcheval

CoRR, 2022

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, Daniel Rueckert, Rickmer Braren

Nat. Mach. Intell., 2021

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, Théo Ryffel, Kritika Prakash, Tom Titcombe, Varun Kumar Khare, Maddie Shang, Ionesio Junior, Animesh Gupta, Jason Paumier, Nahua Kang, Vova Manannikov, Andrew Trask

CoRR, 2021

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

ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing.

Théo Ryffel, David Pointcheval, Francis R. Bach

CoRR, 2020

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, Sara Hooker, Jade Leung, Andrew Trask, Emma Bluemke, Jonathan Lebensold, Cullen O'Keefe, Mark Koren, Théo Ryffel, J. B. Rubinovitz, Tamay Besiroglu, Federica Carugati, Jack Clark, Peter Eckersley, Sarah de Haas, Maritza Johnson, Ben Laurie, Alex Ingerman, Igor Krawczuk, Amanda Askell, Rosario Cammarota, Andrew Lohn, David Krueger, Charlotte Stix, Peter Henderson, Logan Graham, Carina Prunkl, Bianca Martin, Elizabeth Seger, Noa Zilberman, Seán Ó hÉigeartaigh, Frens Kroeger, Girish Sastry, Rebecca Kagan, Adrian Weller, Brian Tse, Elizabeth Barnes, Allan Dafoe, Paul Scharre, Ariel Herbert-Voss, Martijn Rasser, Shagun Sodhani, Carrick Flynn, Thomas Krendl Gilbert, Lisa Dyer, Saif Khan, Yoshua Bengio, Markus Anderljung

CoRR, 2020

2019

Partially Encrypted Machine Learning using Functional Encryption.

Théo Ryffel, Edouard Dufour Sans, Romain Gay, Francis R. Bach, David Pointcheval

CoRR, 2019

Partially Encrypted Deep Learning using Functional Encryption.

Théo Ryffel, David Pointcheval, Francis R. Bach, Edouard Dufour-Sans, Romain Gay

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

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