Publications

Adapting Perioperative Care for Neurodivergent Children - A Scoping Review
Spandana Veeravalli
Maia Michaud
Judy Colton
Brenda Bourdeau
Samantha Sacks
Lindsay Hales
Elena Guadagno
Dan Poenaru
2025-01-31
Journal of Pediatric Surgery (publié)
doi.org
AIoT Smart Home via Autonomous LLM Agents
Dmitriy Rivkin
Francois Hogan
Amal Feriani
Abhisek Konar
Adam Sigal
Xue Liu
Gregory Dudek
2025-01-31
IEEE Internet of Things Journal (publié)
doi.org
Application of deep reinforcement learning for intrusion detection in Internet of Things: A systematic review
Saeid Jamshidi
Amin Nikanjam
Kawser Wazed Nafi
Foutse Khomh
Rasoul Rasta
2025-01-31
Internet of Things (publié)
doi.org
arxiv.org
Isolating the impact of tissue heterogeneities in high dose rate brachytherapy treatment of the breast
Jules Faucher
Vincent Turgeon
Boris Bahoric
S. Enger
Peter G.F. Watson
2025-01-31
Physics and Imaging in Radiation Oncology (publié)
doi.org
Programmable Shape‐Preserving Soft Robotics Arm via Multimodal Multistability (Adv. Funct. Mater. 6/2025)
Benyamin Shahryari
Hossein Mofatteh
Arian Sargazi
Armin Mirabolghasemi
David Meger
Abdolhamid Akbarzadeh
2025-01-31
Advanced Functional Materials (publié)
doi.org
A Scalable Architecture for Future Regenerative Satellite Payloads
Olfa Ben Yahia
Zineb Garroussi
Brunilde Sansò
Jean-François Frigon
Stéphane Martel
Antoine Lesage-Landry
Gunes Karabulut Kurt
This paper addresses the limitations of current satellite payload architectures, which are predominantly hardware-driven and lack the flexib… (voir plus)ility to adapt to increasing data demands and uneven traffic. To overcome these challenges, we present a novel architecture for future regenerative and programmable satellite payloads and utilize interconnected modem banks to promote higher scalability and flexibility. We formulate an optimization problem to efficiently manage traffic among these modem banks and balance the load. Additionally, we provide comparative numerical simulation results, considering end-to-end delay and packet loss analysis. The results illustrate that our proposed architecture maintains lower delays and packet loss even with higher traffic demands and smaller buffer sizes.
2025-01-31
IEEE Wireless Communications Letters (publié)
doi.org
arxiv.org
The Harmonic Exponential Filter for Nonparametric Estimation on Motion Groups
Miguel Saavedra-Ruiz
Steven A. Parkison
Ria Arora
James Richard Forbes
Liam Paull
Bayesian estimation is a vital tool in robotics as it allows systems to update the robot state belief using incomplete information from nois… (voir plus)y sensors. To render the state estimation problem tractable, many systems assume that the motion and measurement noise, as well as the state distribution, are unimodal and Gaussian. However, there are numerous scenarios and systems that do not comply with these assumptions. Existing nonparametric filters that are used to model multimodal distributions have drawbacks that limit their ability to represent a diverse set of distributions. This paper introduces a novel approach to nonparametric Bayesian filtering on motion groups, designed to handle multimodal distributions using harmonic exponential distributions. This approach leverages two key insights of harmonic exponential distributions: a) the product of two distributions can be expressed as the element-wise addition of their log-likelihood Fourier coefficients, and b) the convolution of two distributions can be efficiently computed as the tensor product of their Fourier coefficients. These observations enable the development of an efficient and asymptotically exact solution to the Bayes filter up to the band limit of a Fourier transform. We demonstrate our filter's performance compared with established nonparametric filtering methods across simulated and real-world localization tasks.
2025-01-31
IEEE Robotics and Automation Letters (publié)
doi.org
arxiv.org
La communication financière à l’épreuve de la crise COVID : une gestion des impressions ?
Corinne Bessieux-Ollier
Grégoire Davrinche
Guillaume Dumas
Nous étudions l’impact de la crise du COVID-19 sur la gestion des impressions pratiquée par les entreprises françaises cotées. Cette c… (voir plus)rise ayant eu un impact fort sur l’activité des entreprises, nous observons si les dirigeants modifient la manière de présenter l’information liée aux résultats non-GAAP, à travers l’utilisation de stratégies d’obscurcissement. Les données sur la gestion des impressions ont été collectées manuellement dans les communiqués de résultats annuels des entreprises du SBF 120 sur la période 2018-2020. Nous constatons une diminution générale du niveau de gestion des impressions en période de crise, notamment pour les entreprises des secteurs ayant été les plus impactés par la crise COVID. Cette diminution est toutefois moins prononcée pour les entreprises ayant sous-performé par rapport à leur secteur d’activité et pour les entreprises dont la performance a le plus diminué (indépendamment du secteur auquel elles appartiennent). Nos résultats suggèrent que les entreprises dont la baisse de performance pourrait être attribuée à des causes internes (résultats très défavorables, résultats en deçà du secteur d’activité) demeurent soucieuses de l’image qu’elles renvoient et maintiennent leur niveau de gestion des impressions malgré la crise.
2025-01-28
Comptabilité Contrôle Audit (publié)
doi.org
TEARS: Text Representations for Scrutable Recommendations.
Emiliano Penaloza
Olivier Gouvert
Haolun Wu
Laurent Charlin
Traditional recommender systems rely on high-dimensional (latent) embeddings for modeling user-item interactions, often resulting in opaque … (voir plus)representations that lack interpretability. Moreover, these systems offer limited control to users over their recommendations. Inspired by recent work, we introduce TExtuAl Representations for Scrutable recommendations (TEARS) to address these challenges. Instead of representing a user's interests through a latent embedding, TEARS encodes them in natural text, providing transparency and allowing users to edit them. To do so, TEARS uses a modern LLM to generate user summaries based on user preferences. Using these summaries, we take a hybrid approach where we use an optimal transport procedure to align the summaries' representation with the learned representation of a standard VAE for collaborative filtering. We find this approach can surpass the performance of popular VAE models while providing user-controllable recommendations. We also analyze the controllability of TEARS through three simulated user tasks to evaluate the effectiveness of a user editing its summary. A more detailed version of this manuscript with more experiments, baselines and detail is provided on arXiv.
2025-01-28
ACM.org/TheWebConf/2025/Conference (poster)
doi.org
openreview.net
Causal Discovery in Astrophysics: Unraveling Supermassive Black Hole and Galaxy Coevolution
Zehao Jin
Mario Pasquato
Benjamin L. Davis
Tristan Deleu
Yu Luo
Changhyun Cho
Pablo Lemos
Laurence Perreault-Levasseur
Yoshua Bengio
Xi Kang
Andrea Valerio Maccio
Yashar Hezaveh
Correlation does not imply causation, but patterns of statistical association between variables can be exploited to infer a causal structure… (voir plus) (even with purely observational data) with the burgeoning field of causal discovery. As a purely observational science, astrophysics has much to gain by exploiting these new methods. The supermassive black hole (SMBH)--galaxy interaction has long been constrained by observed scaling relations, that is low-scatter correlations between variables such as SMBH mass and the central velocity dispersion of stars in a host galaxy's bulge. This study, using advanced causal discovery techniques and an up-to-date dataset, reveals a causal link between galaxy properties and dynamically-measured SMBH masses. We apply a score-based Bayesian framework to compute the exact conditional probabilities of every causal structure that could possibly describe our galaxy sample. With the exact posterior distribution, we determine the most likely causal structures and notice a probable causal reversal when separating galaxies by morphology. In elliptical galaxies, bulge properties (built from major mergers) tend to influence SMBH growth, while in spiral galaxies, SMBHs are seen to affect host galaxy properties, potentially through feedback in gas-rich environments. For spiral galaxies, SMBHs progressively quench star formation, whereas in elliptical galaxies, quenching is complete, and the causal connection has reversed. Our findings support theoretical models of hierarchical assembly of galaxies and active galactic nuclei feedback regulating galaxy evolution. Our study suggests the potentiality for further exploration of causal links in astrophysical and cosmological scaling relations, as well as any other observational science.
2025-01-27
The Astrophysical Journal (publié)
doi.org
arxiv.org
The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications
Philippe Brouillard
Chandler Squires
Jonas Wahl
Konrad Paul Kording
Karen Sachs
Alexandre Drouin
Dhanya Sridhar
Causal discovery aims to automatically uncover causal relationships from data, a capability with significant potential across many scientifi… (voir plus)c disciplines. However, its real-world applications remain limited. Current methods often rely on unrealistic assumptions and are evaluated only on simple synthetic toy datasets, often with inadequate evaluation metrics. In this paper, we substantiate these claims by performing a systematic review of the recent causal discovery literature. We present applications in biology, neuroscience, and Earth sciences - fields where causal discovery holds promise for addressing key challenges. We highlight available simulated and real-world datasets from these domains and discuss common assumption violations that have spurred the development of new methods. Our goal is to encourage the community to adopt better evaluation practices by utilizing realistic datasets and more adequate metrics.
2025-01-27
cclear.cc/CLeaR/2025/Conference (poster)
doi.org
proceedings.mlr.press
Associations between circulating amino acids and metabolic dysfunction‐associated steatotic liver disease in individuals living with severe obesity
Ina Maltais‐Payette
Jérôme Bourgault
Marie‐Frédérique Gauthier
Laurent Biertho
Simon Marceau
François Julien
Patricia L. Mitchell
Christian Couture
Francis Brière
J. Corbeil
Benoit J. Arsenault
André Tchernof
2025-01-26
Physiological Reports (publié)
doi.org