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2020 – today
- 2023
[c4]Simon Meoni
, Éric de la Clergerie, Théo Ryffel:
Large Language Models as Instructors: A Study on Multilingual Clinical Entity Extraction. BioNLP@ACL 2023: 178-190- [c3]Simon Meoni, Théo Ryffel, Éric de la Clergerie:
Annotate French Clinical Data Using Large Language Model Predictions. ICHI 2023: 550-557 - [c2]Simon Meoni, Théo Ryffel, Éric Villemonte de la Clergerie:
Annotation d'entités cliniques en utilisant les Larges Modèles de Langue. CORIA-TALN (1) 2023: 190-203 - 2022
- [b1]Théo Ryffel:
Cryptography for Privacy-Preserving Machine Learning. (Cryptographie pour l'apprentissage automatique respectueux de la vie privée). École Normale Supérieure, Paris, France, 2022 - [j2]Théo Ryffel, Pierre Tholoniat, David Pointcheval, Francis R. Bach:
AriaNN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing. Proc. Priv. Enhancing Technol. 2022(1): 291-316 (2022) - [i7]Théo Ryffel, Francis R. Bach, David Pointcheval:
Differential Privacy Guarantees for Stochastic Gradient Langevin Dynamics. CoRR abs/2201.11980 (2022) - 2021
- [j1]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:
End-to-end privacy preserving deep learning on multi-institutional medical imaging. Nat. Mach. Intell. 3(6): 473-484 (2021) - [i6]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:
Syft 0.5: A Platform for Universally Deployable Structured Transparency. CoRR abs/2104.12385 (2021) - 2020
- [i5]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:
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. CoRR abs/2004.07213 (2020) - [i4]Théo Ryffel, David Pointcheval, Francis R. Bach:
ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing. CoRR abs/2006.04593 (2020) - [i3]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:
Privacy-preserving medical image analysis. CoRR abs/2012.06354 (2020)
2010 – 2019
- 2019
- [c1]Théo Ryffel, David Pointcheval, Francis R. Bach, Edouard Dufour-Sans, Romain Gay:
Partially Encrypted Deep Learning using Functional Encryption. NeurIPS 2019: 4519-4530 - [i2]Théo Ryffel, Edouard Dufour Sans, Romain Gay, Francis R. Bach, David Pointcheval:
Partially Encrypted Machine Learning using Functional Encryption. CoRR abs/1905.10214 (2019) - 2018
- [i1]Théo Ryffel, Andrew Trask, Morten Dahl, Bobby Wagner, Jason Mancuso, Daniel Rueckert, Jonathan Passerat-Palmbach:
A generic framework for privacy preserving deep learning. CoRR abs/1811.04017 (2018)
Coauthor Index
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