Search Results for author: Margaux Luck

Found 11 papers, 5 papers with code

Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes

no code implementations7 Sep 2022 Alex Fedorov, Eloy Geenjaar, Lei Wu, Tristan Sylvain, Thomas P. DeRamus, Margaux Luck, Maria Misiura, R Devon Hjelm, Sergey M. Plis, Vince D. Calhoun

Coarse labels do not capture the long-tailed spectrum of brain disorder phenotypes, which leads to a loss of generalizability of the model that makes them less useful in diagnostic settings.

Self-Supervised Learning

On self-supervised multi-modal representation learning: An application to Alzheimer's disease

no code implementations25 Dec 2020 Alex Fedorov, Lei Wu, Tristan Sylvain, Margaux Luck, Thomas P. DeRamus, Dmitry Bleklov, Sergey M. Plis, Vince D. Calhoun

In this paper, we introduce a way to exhaustively consider multimodal architectures for contrastive self-supervised fusion of fMRI and MRI of AD patients and controls.

General Classification Representation 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

Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments

1 code implementation29 Oct 2019 Martin Weiss, Simon Chamorro, Roger Girgis, Margaux Luck, Samira E. Kahou, Joseph P. Cohen, Derek Nowrouzezahrai, Doina Precup, Florian Golemo, Chris Pal

In our endeavor to create a navigation assistant for the BVI, we found that existing Reinforcement Learning (RL) environments were unsuitable for the task.

Navigate Reinforcement Learning (RL)

Learning to rank for censored survival data

1 code implementation6 Jun 2018 Margaux Luck, Tristan Sylvain, Joseph Paul Cohen, Heloise Cardinal, Andrea Lodi, Yoshua Bengio

Survival analysis is a type of semi-supervised ranking task where the target output (the survival time) is often right-censored.

Learning-To-Rank Survival Analysis

Distribution Matching Losses Can Hallucinate Features in Medical Image Translation

1 code implementation22 May 2018 Joseph Paul Cohen, Margaux Luck, Sina Honari

When the output of an algorithm is a transformed image there are uncertainties whether all known and unknown class labels have been preserved or changed.

Image Generation Translation

Rule-Mining based classification: a benchmark study

1 code implementation30 Jun 2017 Margaux Luck, Nicolas Pallet, Cecilia Damon

This study proposed an exhaustive stable/reproducible rule-mining algorithm combined to a classifier to generate both accurate and interpretable models.

Classification General Classification +1

Deep Learning for Patient-Specific Kidney Graft Survival Analysis

2 code implementations29 May 2017 Margaux Luck, Tristan Sylvain, Héloïse Cardinal, Andrea Lodi, Yoshua Bengio

An accurate model of patient-specific kidney graft survival distributions can help to improve shared-decision making in the treatment and care of patients.

Decision Making Multi-Task Learning +1

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