Publications

Atlas-Based Quantification of DTI Measures in a Typically Developing Pediatric Spinal Cord
Shiva Shahrampour
Benjamin De Leener
Mahdi Alizadeh
D. Middleton
Laura Krisa
Adam E. Flanders
S. Faro
Julien Cohen-Adad
F. Mohamed
2021-07-29
American Journal of Neuroradiology (published)
doi.org
Educating the future generation of researchers: A cross-disciplinary survey of trends in analysis methods
Taylor Bolt
Jason S. Nomi
Danilo Bzdok
Lucina Q. Uddin
2021-07-29
PLoS Biology (published)
doi.org
Human brain anatomy reflects separable genetic and environmental components of socioeconomic status
H. Kweon
Gökhan Aydogan
Alain Dagher
Danilo Bzdok
C. Ruff
Gideon Nave
Martha J Farah
Philipp Koellinger
Recent studies report that socioeconomic status (SES) correlates with brain structure. Yet, such findings are variable and little is known a… (see more)bout underlying causes. We present a well-powered voxel-based analysis of grey matter volume (GMV) across levels of SES, finding many small SES effects widely distributed across the brain, including cortical, subcortical and cerebellar regions. We also construct a polygenic index of SES to control for the additive effects of common genetic variation related to SES, which attenuates observed SES-GMV relations, to different degrees in different areas. Remaining variance, which may be attributable to environmental factors, is substantially accounted for by body mass index, a marker for lifestyle related to SES. In sum, SES affects multiple brain regions through measurable genetic and environmental effects. One-sentence Summary Socioeconomic status is linked with brain anatomy through a varying balance of genetic and environmental influences.
2021-07-29
bioRxiv (preprint)
doi.org
Local Structure Matters Most: Perturbation Study in NLU
Louis Clouâtre
Prasanna Parthasarathi
Amal Zouaq
Sarath Chandar
Recent research analyzing the sensitivity of natural language understanding models to word-order perturbations has shown that neural models … (see more)are surprisingly insensitive to the order of words.In this paper, we investigate this phenomenon by developing order-altering perturbations on the order of words, subwords, and characters to analyze their effect on neural models’ performance on language understanding tasks.We experiment with measuring the impact of perturbations to the local neighborhood of characters and global position of characters in the perturbed texts and observe that perturbation functions found in prior literature only affect the global ordering while the local ordering remains relatively unperturbed.We empirically show that neural models, invariant of their inductive biases, pretraining scheme, or the choice of tokenization, mostly rely on the local structure of text to build understanding and make limited use of the global structure.
2021-07-29
ArXiv (preprint)
doi.org
arxiv.org
Clones in deep learning code: what, where, and why?
Hadhemi Jebnoun
Md. Saidur Rahman
Foutse Khomh
Biruk Asmare Muse
2021-07-28
ArXiv (preprint)
doi.org
arxiv.org
Automated Data-Driven Generation of Personalized Pedagogical Interventions in Intelligent Tutoring Systems
Ekaterina Kochmar
Dung D. Vu
Robert Belfer
Varun Gupta
Iulian V. Serban
Joelle Pineau
2021-07-27
International Journal of Artificial Intelligence in Education (published)
doi.org
Automated Data-Driven Generation of Personalized Pedagogical Interventions in Intelligent Tutoring Systems
Ekaterina Kochmar
Dung D. Vu
Robert Belfer
Varun Gupta
Iulian V. Serban
Joelle Pineau
2021-07-27
International Journal of Artificial Intelligence in Education (published)
doi.org
Geographical concentration of COVID-19 cases by social determinants of health in 16 large metropolitan areas in Canada - a cross-sectional study
Yiqing Xia
Huiting Ma
Gary Moloney
Héctor A. Velásquez García
Monica Sirski
Naveed Janjua
David Vickers
Tyler Williamson
Alan Katz
Kristy Yu
Rafal Kustra
David Buckeridge
Marc Brisson
Stefan Baral
Sharmistha Mishra
Mathieu Maheu-Giroux
Background: There is a growing recognition that strategies to reduce SARS-CoV-2 transmission should be responsive to local transmission dyna… (see more)mics. Studies have revealed inequalities along social determinants of health, but little investigation was conducted surrounding geographic concentration within cities. We quantified social determinants of geographic concentration of COVID-19 cases across sixteen census metropolitan areas (CMA) in four Canadian provinces. Methods: We used surveillance data on confirmed COVID-19 cases at the level of dissemination area. Gini (co-Gini) coefficients were calculated by CMA based on the proportion of the population in ranks of diagnosed cases and each social determinant using census data (income, education, visible minority, recent immigration, suitable housing, and essential workers) and the corresponding share of cases. Heterogeneity was visualized using Lorenz (concentration) curves. Results: Geographic concentration was observed in all CMAs (half of the cumulative cases were concentrated among 21-35% of each city's population): with the greatest geographic heterogeneity in Ontario CMAs (Gini coefficients, 0.32-0.47), followed by British Columbia (0.23-0.36), Manitoba (0.32), and Quebec (0.28-0.37). Cases were disproportionately concentrated in areas with lower income, education attainment, and suitable housing; and higher proportion of visible minorities, recent immigrants, and essential workers. Although a consistent feature across CMAs was concentration by proportion visible minorities, the magnitude of concentration by social determinants varied across CMAs. Interpretation: The feature of geographical concentration of COVID-19 cases was consistent across CMAs, but the pattern by social determinants varied. Geographically-prioritized allocation of resources and services should be tailored to the local drivers of inequalities in transmission in response to SARS-CoV-2's resurgence.
2021-07-26
medRxiv (preprint)
doi.org
Modelling Latent Translations for Cross-Lingual Transfer
Edoardo Ponti
Julia Kreutzer
Ivan Vulić
Siva Reddy
2021-07-23
ArXiv (preprint)
arxiv.org
arxiv.org
Automatic multiclass intramedullary spinal cord tumor segmentation on MRI with deep learning
Andreanne Lemay
Charley Gros
Zhizheng Zhuo
Jie Zhang
Yunyun Duan
Julien Cohen-Adad
Yaou Liu
2021-07-22
NeuroImage : Clinical (published)
doi.org
Exploration-Driven Representation Learning in Reinforcement Learning
Akram Erraqabi
Harry Zhao
Mingde Zhao
Marlos C. Machado
Yoshua Bengio
Sainbayar Sukhbaatar
Ludovic Denoyer
Alessandro Lazaric
Learning reward-agnostic representations is an emerging paradigm in reinforcement learning. These representations can be leveraged for sever… (see more)al purposes ranging from reward shaping to skill discovery. Nevertheless, in order to learn such representations, existing methods often rely on assuming uniform access to the state space. With such a privilege, the agent’s coverage of the environment can be limited which hurts the quality of the learned representations. In this work, we introduce a method that explicitly couples representation learning with exploration when the agent is not provided with a uniform prior over the state space. Our method learns representations that constantly drive exploration while the data generated by the agent’s exploratory behavior drives the learning of better representations. We empirically validate our approach in goal-achieving tasks, demonstrating that the learned representation captures the dynamics of the environment, leads to more accurate value estimation, and to faster credit assignment, both when used for control and for reward shaping. Finally, the exploratory policy that emerges from our approach proves to be successful at continuous navigation tasks with sparse rewards.
2021-07-22
ICML.cc/2021/Workshop/URL (poster)
openreview.net
openreview.net
Diffusion magnetic resonance imaging reveals tract‐specific microstructural correlates of electrophysiological impairments in non‐myelopathic and myelopathic spinal cord compression
Jan Valosek
René Labounek
Tomáš Horák
Magda Horáková
Petr Bednařík
Miloš Keřkovský
Jan Kočica
Tomáš Rohan
Christophe Lenglet
Julien Cohen-Adad
Petr Hluštík
Eva Vlčková
Zdeněk Kadaňka
Josef Bednařík
Alena Svatkova
Non‐myelopathic degenerative cervical spinal cord compression (NMDC) frequently occurs throughout aging and may progress to potentially ir… (see more)reversible degenerative cervical myelopathy (DCM). Whereas standard clinical magnetic resonance imaging (MRI) and electrophysiological measures assess compression severity and neurological dysfunction, respectively, underlying microstructural deficits still have to be established in NMDC and DCM patients. The study aims to establish tract‐specific diffusion MRI markers of electrophysiological deficits to predict the progression of asymptomatic NMDC to symptomatic DCM.
2021-07-21
European Journal of Neurology (published)
doi.org