Search Results for author: Francis Dutil

Found 15 papers, 7 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

Cross-Modal Information Maximization for Medical Imaging: CMIM

no code implementations20 Oct 2020 Tristan Sylvain, Francis Dutil, Tess Berthier, Lisa Di Jorio, Margaux Luck, Devon Hjelm, Yoshua Bengio

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 patient undergoes (CT scans, MRI, PET, Ultrasound, etc.)

Image Classification Medical Image Classification

FoCL: Feature-Oriented Continual Learning for Generative Models

1 code implementation9 Mar 2020 Qicheng Lao, Mehrzad Mortazavi, Marzieh Tahaei, Francis Dutil, Thomas Fevens, Mohammad Havaei

In this paper, we propose a general framework in continual learning for generative models: Feature-oriented Continual Learning (FoCL).

Continual Learning Incremental Learning

The TCGA Meta-Dataset Clinical Benchmark

1 code implementation18 Oct 2019 Mandana Samiei, Tobias Würfl, Tristan Deleu, Martin Weiss, Francis Dutil, Thomas Fevens, Geneviève Boucher, Sebastien Lemieux, Joseph Paul Cohen

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

Decision Making

Saliency is a Possible Red Herring When Diagnosing Poor Generalization

1 code implementation ICLR 2021 Joseph D. Viviano, Becks Simpson, Francis Dutil, Yoshua Bengio, Joseph Paul Cohen

In some prediction tasks, such as for medical images, one may have some images with masks drawn by a human expert, indicating a region of the image containing relevant information to make the prediction.

General Classification

Underwhelming Generalization Improvements From Controlling Feature Attribution

no code implementations25 Sep 2019 Joseph D Viviano, Becks Simpson, Francis Dutil, Yoshua Bengio, Joseph Paul Cohen

We describe a simple method for taking advantage of such auxiliary labels, by training networks to ignore the distracting features which may be extracted outside of the region of interest, on the training images for which such masks are available.

GradMask: Reduce Overfitting by Regularizing Saliency

no code implementations16 Apr 2019 Becks Simpson, Francis Dutil, Yoshua Bengio, Joseph Paul Cohen

With too few samples or too many model parameters, overfitting can inhibit the ability to generalise predictions to new data.

Lesion Segmentation

InfoMask: Masked Variational Latent Representation to Localize Chest Disease

no code implementations28 Mar 2019 Saeid Asgari Taghanaki, Mohammad Havaei, Tess Berthier, Francis Dutil, Lisa Di Jorio, Ghassan Hamarneh, Yoshua Bengio

The scarcity of richly annotated medical images is limiting supervised deep learning based solutions to medical image analysis tasks, such as localizing discriminatory radiomic disease signatures.

Multiple Instance Learning

Towards the Latent Transcriptome

1 code implementation8 Oct 2018 Assya Trofimov, Francis Dutil, Claude Perreault, Sebastien Lemieux, Yoshua Bengio, Joseph Paul Cohen

In this work we propose a method to compute continuous embeddings for kmers from raw RNA-seq data, without the need for alignment to a reference genome.

Towards Gene Expression Convolutions using Gene Interaction Graphs

1 code implementation18 Jun 2018 Francis Dutil, Joseph Paul Cohen, Martin Weiss, Georgy Derevyanko, Yoshua Bengio

We find this approach provides an advantage for particular tasks in a low data regime but is very dependent on the quality of the graph used.

Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder

1 code implementation13 Jun 2017 Caglar Gulcehre, Francis Dutil, Adam Trischler, Yoshua Bengio

We investigate the integration of a planning mechanism into an encoder-decoder architecture with an explicit alignment for character-level machine translation.

Machine Translation Translation

Adversarial Generation of Natural Language

no code implementations WS 2017 Sai Rajeswar, Sandeep Subramanian, Francis Dutil, Christopher Pal, Aaron Courville

Generative Adversarial Networks (GANs) have gathered a lot of attention from the computer vision community, yielding impressive results for image generation.

Image Generation Language Modelling +1

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