151 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Polytechnique MontréalCA7 papers
- McGill UniversityCA6 papers
- Université de MontréalCA5 papers
- Mila - Quebec Artificial Intelligence InstituteCA4 papers
- Montreal Neurological Institute and HospitalCA3 papers
- University of CalgaryCA2 papers
- AIDS VancouverCA1 paper
- BC Centre for Disease ControlCA1 paper
- Canadian Institute for Advanced ResearchCA1 paper
- CentraleSupélecFR1 paper
- Centre for Human GeneticsGB1 paper
- Centre for Research in Astrophysics of QuébecCA1 paper
11 papers
Robustness of Neural Ratio and Posterior Estimators to Distributional Shifts for Population-Level Dark Matter Analysis in Strong Gravitational Lensing
Andreas Filipp, Yashar Hezaveh, Laurence Perreault-Levasseur
We investigate the robustness of Neural Ratio Estimators (NREs) and Neural Posterior Estimators (NPEs) to distributional shifts in the context of measuring the abundance of dark ma…
The Canadian VirusSeq Data Portal & Duotang: open resources for SARS-CoV-2 viral sequences and genomic epidemiology
Erin E. Gill, Baofeng Jia, Carmen Lia Murall +67
The COVID-19 pandemic led to a large global effort to sequence SARS-CoV-2 genomes from patient samples to track viral evolution and inform public health response. Millions of SARS-…
Towards Transcranial 3D Ultrasound Localization Microscopy of the Nonhuman Primate Brain
Paul Xing, Vincent Perrot, Adan Ulises Dominguez-Vargas +3
Hemodynamic changes occur in stroke and neurodegenerative diseases. Developing imaging techniques allowing the in vivo visualization and quantification of cerebral blood flow would…
Pruning Sparse Tensor Neural Networks Enables Deep Learning for 3D Ultrasound Localization Microscopy
Brice Rauby, Paul Xing, Jonathan Porée +2
Ultrasound Localization Microscopy (ULM) is a non-invasive technique that allows for the imaging of micro-vessels in vivo, at depth and with a resolution on the order of ten micron…
Sparse channel sampling for ultrasound localization microscopy (SPARSE-ULM)
Erwan Hardy, Jonathan Poree, Hatim Belgharbi +3
Ultrasound Localization Microscopy (ULM) has recently enabled the mapping of the cerebral vasculature in vivo with a resolution ten times smaller than the wavelength used, down to…
Equivalent Time Active Cavitation Imaging
Simon Blais, Jonathan Poree, Gerardo Ramos-Palacios +4
The development of neurologically active drugs faces a challenge in treating brain diseases due to the blood-brain barrier's impermeability. High-intensity focused ultrasound can o…
A Deep Learning Framework for Spatiotemporal Ultrasound Localization Microscopy
Léo Milecki, Jonathan Porée, Hatim Belgharbi +6
Ultrasound Localization Microscopy can resolve the microvascular bed down to a few micrometers. To achieve such performance microbubble contrast agents must perfuse the entire micr…
Equivalent-Time-Active-Cavitation-Imaging Enables Vascular-Resolution Blood-Brain-Barrier-Opening-Therapy Planning
Samuel Desmarais, Gerardo Ramos-Palacios, Jonathan Poree +4
Linking cavitation and anatomy was found to be important for predictable outcomes in Focused-Ultrasound Blood-Brain-Barrier-Opening and requires high resolution cavitation mapping.…
Planning in Dynamic Environments with Conditional Autoregressive Models
Johanna Hansen, Kyle Kastner, Aaron Courville +1
We demonstrate the use of conditional autoregressive generative models (van den Oord et al., 2016a) over a discrete latent space (van den Oord et al., 2017b) for forward planning w…
Promise and pitfalls of g-ratio estimation with MRI
Jennifer S. W. Campbell, Ilana R. Leppert, Mathieu Boudreau +5
The fiber g-ratio is the ratio of the inner to the outer diameter of the myelin sheath of a myelinated axon. It has a limited dynamic range in healthy white matter, as it is optimi…
Diet Networks: Thin Parameters for Fat Genomics
Adriana Romero, Pierre Luc Carrier, Akram Erraqabi +7
Learning tasks such as those involving genomic data often poses a serious challenge: the number of input features can be orders of magnitude larger than the number of training exam…