Search Results for author: Florent Chandelier

Found 2 papers, 0 papers with code

Application of Homomorphic Encryption in Medical Imaging

no code implementations12 Oct 2021 Francis Dutil, Alexandre See, Lisa Di Jorio, Florent Chandelier

In this technical report, we explore the use of homomorphic encryption (HE) in the context of training and predicting with deep learning (DL) models to deliver strict \textit{Privacy by Design} services, and to enforce a zero-trust model of data governance.

Federated Learning

Adversarially Learned Mixture Model

no code implementations14 Jul 2018 Andrew Jesson, Cécile Low-Kam, Tanya Nair, Florian Soudan, Florent Chandelier, Nicolas Chapados

The Adversarially Learned Mixture Model (AMM) is a generative model for unsupervised or semi-supervised data clustering.

Clustering

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