| 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 | 460 | 2018 |
| 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 | 325 | 2020 |
| 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 | 258 | 2021 |
| Pysyft: A library for easy federated learning A Ziller, A Trask, A Lopardo, B Szymkow, B Wagner, E Bluemke, ... Federated learning systems: Towards next-generation AI, 111-139, 2021 | 162 | 2021 |
| 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 | 73 | 2020 |
| Partially encrypted deep learning using functional encryption T Ryffel, D Pointcheval, F Bach, E Dufour-Sans, R Gay Advances in Neural Information Processing Systems 32, 2019 | 44 | 2019 |
| Partially encrypted machine learning using functional encryption T Ryffel, E Dufour-Sans, R Gay, F Bach, D Pointcheval arXiv preprint arXiv:1905.10214, 2019 | 43 | 2019 |
| Toward trustworthy AI development: mechanisms for supporting verifiable claims (2020) M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ... arXiv preprint arXiv:2004.07213, 2020 | 17 | 2020 |
| Differential privacy guarantees for stochastic gradient langevin dynamics T Ryffel, F Bach, D Pointcheval arXiv preprint arXiv:2201.11980, 2022 | 15 | 2022 |
| 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 | 11 | 2021 |
| A generic framework for privacy preserving deep learning. arXiv T Ryffel, A Trask, M Dahl, B Wagner, J Mancuso, D Rueckert, ... arXiv preprint arXiv:1811.04017, 2018 | 10 | 2018 |
| Privacy-preserving medical image analysis A Ziller, J Passerat-Palmbach, T Ryffel, D Usynin, A Trask, IDLC Junior, ... arXiv preprint arXiv:2012.06354, 2020 | 9 | 2020 |
| Large language models as instructors: A study on multilingual clinical entity extraction S Meoni, E De la Clergerie, T Ryffel The 22nd Workshop on Biomedical Natural Language Processing and BioNLP …, 2023 | 7 | 2023 |
| Cryptography for Privacy-Preserving Machine Learning T Ryffel ENS Paris-Ecole Normale Supérieure de Paris, 2022 | 1 | 2022 |
| Annotate French Clinical Data Using Large Language Model Predictions S Meoni, T Ryffel, É De La Clergerie 2023 IEEE 11th International Conference on Healthcare Informatics (ICHI …, 2023 | | 2023 |
| Annotation d'entités cliniques en utilisant les Larges Modèles de Langue S Meoni, T Ryffel, E De La Clergerie 18e Conférence en Recherche d'Information et Applications\\16e Rencontres …, 2023 | | 2023 |
| Cryptography for Privacy-Preserving Machine Learning T Ryffel | | |
Andrew TraskUniversity of Oxford and OpenMinedVerified email at openmined.org
