Posts by Collection

Processus de coalescence pour un échantillon stratifié

Unpublished work, 2011

Utilisation des modèles de semi-Markov cachés à des fins d’amélioration d’intelligences artificielles dans les jeux vidéo

Unpublished work, 2013

Utilisation des modèles de Markov cachés dans l’objectif de modéliser certaines séries chronologiques

Unpublished work, 2014

Statistical Learning Techniques : A review

Unpublished work, 2016

Inference on latent variable models

Unpublished work, 2017

Controllable content generation

Unpublished work, 2019

Variational Autoencoders: theory, implementation and unanswered questions

Unpublished work, 2019

The integration of functional data analysis in conditional image generation

Unpublished work, 2022

Controllable content generator (Best Poster Award)

Published: April 25, 2019

A Linear State-Space Model to Predict Hourly Electricity Demand

Published: June 01, 2020

Neural Networks with Functional Responses (Poster Presentation Award)

Published: May 30, 2022

Deep-Learning-Based Multi-modal Survival Analysis for Alzheimer’s Disease

Published: June 20, 2022

Predicting Alzheimer’s disease progression in healthy and MCI subjects using multi-modal deep learning approach

Published: August 01, 2022

Narrow Artificial Intelligence with Machine Learning for Real-Time Estimation of a Mobile Agents Location Using Hidden Markov Models

Cédric Beaulac and Fabrice Larribe

Published in International Journal of Computer Games Technology, February 2017

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A Deep Latent-Variable Model Application to Select Treatment Intensity in Survival Analysis

Cédric Beaulac, Jeffrey S. Rosenthal and David Hodgson

Published in Proceedings of the Machine Learning for Health (ML4H) Workshop at NeurIPS 2018, December 2018

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Predicting University Students’ Academic Success and Major using Random Forests

Cédric Beaulac and Jeffrey S. Rosenthal

Published in Research in Higher Education, January 2019

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BEST : A decision tree algorithm that handles missing values

Cédric Beaulac and Jeffrey S. Rosenthal

Published in Computational Statistics, April 2020

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An evaluation of machine learning techniques to predict the outcome of children treated for Hodgkin-Lymphoma on the AHOD0031 trial

Cédric Beaulac, Jeffrey S. Rosenthal, Qinglin Pei, Debra Friedman, Suzanne Wolden and David Hodgson

Published in Applied Artificial Intelligence, October 2020

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Predicting Time-to-conversion for Dementia of Alzheimer’s Type using Multi-modal Deep Survival Analysis

Ghazal Mirabnahrazam, Da Ma, Cédric Beaulac, Sieun Lee, Karteek Popuri, Hyunwoo Lee, Jiguo Cao, James E Galvin, Lei Wang and Mirza Faisal Beg

Published in Neurobiology of Aging, January 2023

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Introducing a new high-resolution hand-written digits data set with writer characteristics

Cédric Beaulac and Jeffrey S. Rosenthal

Published in SN Computer Science, January 2023

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A moment-matching metric for latent variable generative models

Cédric Beaulac

Published in Machine Learning, June 2023

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Neuroimaging Feature Extraction using a Neural Network Classifier for Imaging Genetics

Cédric Beaulac, Sidi Wu, Erin Gibson, Michelle F. Miranda, Jiguo Cao, Leno Rocha, Mirza Faisal Beg and Farouk S. Nathoo

Published in BMC Bioinformatics, June 2023

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Neural Networks for Scalar Input and Functional Output

Sidi Wu, Cédric Beaulac and Jiguo Cao

Published in Statistics and Computing, August 2023

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Constructing Ancestral Recombination Graphs through Reinforcement Learning

Mélanie Raymond, Marie-Hélène Descary, Cédric Beaulac and Fabrice Larribe

Preprint submitted for review.

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Functional Autoencoder for Smoothing and Representation Learning

Sidi Wu, Cédric Beaulac and Jiguo Cao

Published in Statistics and Computing, October 2024

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Estimation de la position d’un agent mobile dans un environnement bornée grâce aux modèles de Markov cachés.

Published: July 02, 2015

Utilisation des chaînes de Markov cachés pour estimer la position d’un agent mobile.

Published: January 14, 2017

Handling Missing Values with BEST

Published: June 06, 2018

Génération d’images : Une application de l’apprentissage automatique.

Published: March 15, 2019

Auto-encodeur variationnel: vers de nouvelles applications et une mise à jour de la théorie.

Published: November 05, 2020

Performance and accessibility of statistical learning algorithms for applied data analysis.

Published: December 18, 2020

Démystifier les réseaux de neurones

Published: May 05, 2021

Variational Autoencoders: an introduction to new applications and a new regularization approach.

Published: October 13, 2021

Neural Network Disease Classification Based Feature Extraction for Imaging Genetics.

Published: June 03, 2022

Developing neural network architectures for functional data analysis

Published: May 29, 2023

Integrating Deep Learning into Functional Data Analysis

Published: July 13, 2023

Neural network architectures for functional data analysis

Published: October 20, 2023

Functional machine learning and applications

Published: December 16, 2023

Images, pixels, statistique et formes

Published: May 25, 2024

Yasaman Shahhosseini

Ph.D at University of Victoria, started in September 2021

Ghazal Mirabnahrazam

MS.c at Simon Fraser University, completed in August 2022

Hélène Fourniotis

MS.c at Université du Québec à Montréal, started in September 2023

Sabrina Nunes

MS.c at Université du Québec à Montréal, started in September 2023

Valentin Larchevêque

Research Intern at Université du Québec à Montréal, completed in September 2023

Issam Moindjié

Postdoctoral fellow at Université du Québec à Montréal, started in May 2024

Louis-Pierre Ménard

, , 2024

Mélanie Raymond

Ph.D at Université du Québec à Montréal, started in September 2024

Sidi Wu

Ph.D at Simon Fraser University, completed in October 2024