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| 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 | 90 | 2020 |
| Partially encrypted machine learning using functional encryption T Ryffel, E Dufour-Sans, R Gay, F Bach, D Pointcheval arXiv preprint arXiv:1905.10214, 2019 | 33 | 2019 |
| 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 | 32 | 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 | 12 | 2020 |
| 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 | 5 | 2021 |
| Privacy-preserving medical image analysis A Ziller, J Passerat-Palmbach, T Ryffel, D Usynin, A Trask, IDLC Junior, ... arXiv preprint arXiv:2012.06354, 2020 | 3 | 2020 |
| 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 | 2 | 2021 |
