Processus de coalescence pour un échantillon stratifié
Unpublished work, 2011
Posts by Collection
miscellaneous
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Unpublished work, 2013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Unpublished work, 2014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Unpublished work, 2016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Unpublished work, 2017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Unpublished work, 2019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Unpublished work, 2019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Unpublished work, 2022
Comparing shape-based and pixel-based approaches for melanoma detection
Unpublished work, 2026
Boosting for Time Series and an Application to Value at Risk Forecasting
Unpublished work, 2026
posters
publications
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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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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A Functional Approach to Curve Alignment and Shape Analysis
Issam-Ali Moindjié, Cédric Beaulac and Marie-Hélène Descary
Preprint submitted for review.
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Constructing Ancestral Recombination Graphs through Reinforcement Learning
Mélanie Raymond, Marie-Hélène Descary, Cédric Beaulac and Fabrice Larribe
Published in Frontiers in Genetics - Computational Genomics, April 2025
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A Wavelet-Based Framework for Mapping Long Memory in Resting-State fMRI: Age-Related Changes in the Hippocampus from the ADHD-200 Datasets
Yasaman Shahhosseni, Cédric Beaulac, Farouk Nathoo and Michelle F. Miranda
Preprint submitted for review.
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Multivariate Planar Curves: A Statistical Framework for Shape Analysis in Images
Issam-Ali Moindjié, Marie-Hélène Descary and Cédric Beaulac
Preprint submitted for review.
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Shape-Based Inductive Bias for Glioma Grading from Tumor Contours
Puneet Velidi, Michelle F. Miranda, Farouk Nathoo, Ashery Mbilinyi and Cédric Beaulac
Preprint submitted for review.
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talks
Handling Missing Values with BEST
Published:
Auto-encodeur variationnel: vers de nouvelles applications et une mise à jour de la théorie.
Published:
Performance and accessibility of statistical learning algorithms for applied data analysis.
Published:
Démystifier les réseaux de neurones
Published:
Variational Autoencoders: an introduction to new applications and a new regularization approach.
Published:
Functional machine learning and applications
Published:
Images, pixels, statistique et formes
Published:
Functional Representations of Images for Statistical Learning: Shapes, Surfaces, and Beyond
Published:
teaching
Yasaman Shahhosseini
Ph.D at University of Victoria, started in September 2021
Ghazal Mirabnahrazam
MS.c at Simon Fraser University, completed in August 2022
Valentin Larchevêque
Research Intern at Université du Québec à Montréal, completed in September 2023
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
Louis-Pierre Ménard
MS.c at Université du Québec à Montréal, started in September 2025
Issam A. Moindjié
Postdoctoral fellow at Université du Québec à Montréal, completed in September 2025
Andréa Davila
Research Intern at Université du Québec à Montréal, completed in September 2025
Kevin Wang
Research Intern at Université de Montréal, completed in August 2026
Mustapha Labhar
MS.c at Université du Québec à Montréal, started in September 2026