activity
20172021
most citedAdversarial Generation of Natural Language

101 citations · 186 across the 13 of their papers we have counts for

collaborators

13 papers

eess.IV2021★ 2 cited

Application of Homomorphic Encryption in Medical Imaging

Francis Dutil, Alexandre See, Lisa Di Jorio +1

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{Priva…

cs.CV2020★ 4 cited

Cross-Modal Information Maximization for Medical Imaging: CMIM

Tristan Sylvain, Francis Dutil, Tess Berthier +4

In hospitals, data are siloed to specific information systems that make the same information available under different modalities such as the different medical imaging exams the pa…

cs.CV2020

FoCL: Feature-Oriented Continual Learning for Generative Models

Qicheng Lao, Mehrzad Mortazavi, Marzieh Tahaei +3

In this paper, we propose a general framework in continual learning for generative models: Feature-oriented Continual Learning (FoCL). Unlike previous works that aim to solve the c…

cs.LG2019★ 6 cited

The TCGA Meta-Dataset Clinical Benchmark

Mandana Samiei, Tobias Würfl, Tristan Deleu +6

Machine learning is bringing a paradigm shift to healthcare by changing the process of disease diagnosis and prognosis in clinics and hospitals. This development equips doctors and…

cs.CV2019★ 14 cited

Saliency is a Possible Red Herring When Diagnosing Poor Generalization

Joseph D. Viviano, Becks Simpson, Francis Dutil +2

Poor generalization is one symptom of models that learn to predict target variables using spuriously-correlated image features present only in the training distribution instead of…

cs.CV2019★ 5 cited

Dual Adversarial Inference for Text-to-Image Synthesis

Qicheng Lao, Mohammad Havaei, Ahmad Pesaranghader +3

Synthesizing images from a given text description involves engaging two types of information: the content, which includes information explicitly described in the text (e.g., color,…