Jason Mancuso

According to our database, Jason Mancuso authored at least 6 papers between 2018 and 2021.

Collaborative distances:

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

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

2020

Privacy-preserving collaborative machine learning on genomic data using TensorFlow.

Cheng Hong, Zhicong Huang, Wen-jie Lu, Hunter Qu, Li Ma, Morten Dahl, Jason Mancuso

IACR Cryptol. ePrint Arch., 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

2019

Detecting Spiky Corruption in Markov Decision Processes.

Jason Mancuso, Tomasz Kisielewski, David Lindner, Alok Singh

Proceedings of the Workshop on Artificial Intelligence Safety 2019 co-located with the 28th International Joint Conference on Artificial Intelligence, 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

Private Machine Learning in TensorFlow using Secure Computation.

Morten Dahl, Jason Mancuso, Yann Dupis, Ben Decoste, Morgan Giraud, Ian Livingstone, Justin Patriquin, Gavin Uhma

CoRR, 2018