Théo Ryffel
Théo Ryffel
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A generic framework for privacy preserving deep learning
T Ryffel, A Trask, M Dahl, B Wagner, J Mancuso, D Rueckert, ...
arXiv preprint arXiv:1811.04017, 2018
2292018
Toward trustworthy AI development: mechanisms for supporting verifiable claims
M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ...
arXiv preprint arXiv:2004.07213, 2020
902020
Partially encrypted machine learning using functional encryption
T Ryffel, E Dufour-Sans, R Gay, F Bach, D Pointcheval
arXiv preprint arXiv:1905.10214, 2019
332019
End-to-end privacy preserving deep learning on multi-institutional medical imaging
G Kaissis, A Ziller, J Passerat-Palmbach, T Ryffel, D Usynin, A Trask, ...
Nature Machine Intelligence 3 (6), 473-484, 2021
322021
Ariann: Low-interaction privacy-preserving deep learning via function secret sharing
T Ryffel, P Tholoniat, D Pointcheval, F Bach
arXiv preprint arXiv:2006.04593, 2020
122020
PySyft: A Library for Easy Federated Learning
A Ziller, A Trask, A Lopardo, B Szymkow, B Wagner, E Bluemke, ...
Federated Learning Systems, 111-139, 2021
52021
Privacy-preserving medical image analysis
A Ziller, J Passerat-Palmbach, T Ryffel, D Usynin, A Trask, IDLC Junior, ...
arXiv preprint arXiv:2012.06354, 2020
32020
Syft 0.5: A Platform for Universally Deployable Structured Transparency
AJ Hall, M Jay, T Cebere, B Cebere, KL van der Veen, G Muraru, T Xu, ...
arXiv preprint arXiv:2104.12385, 2021
22021
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