1.5k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Université de MontréalCA125 papers
- McGill UniversityCA59 papers
- Polytechnique MontréalCA27 papers
- Flatiron Health (United States)US24 papers
- Flatiron Institute23 papers
- Centre National de la Recherche ScientifiqueFR22 papers
- University of TorontoCA16 papers
- Canadian Institute for Advanced ResearchCA14 papers
- Université Paris-SaclayFR14 papers
- University of AmsterdamNL13 papers
- University of WaterlooCA13 papers
- Centre for Research in Astrophysics of QuébecCA12 papers
25 papers · 1 filter
BARVINN: Arbitrary Precision DNN Accelerator Controlled by a RISC-V CPU
Mohammadhossein Askarihemmat, Sean Wagner, Olexa Bilaniuk +3
We present a DNN accelerator that allows inference at arbitrary precision with dedicated processing elements that are configurable at the bit level. Our DNN accelerator has 8 Proce…
The Dark Energy Survey Year 3 and eBOSS: constraining galaxy intrinsic alignments across luminosity and colour space
S. Samuroff, R. Mandelbaum, J. Blazek +104
We present direct constraints on galaxy intrinsic alignments using the Dark Energy Survey Year 3 (DES Y3), the Extended Baryon Oscillation Spectroscopic Survey (eBOSS) and its prec…
Morphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey
Aritra Ghosh, C. Megan Urry, Aayush Mishra +10
We use the Galaxy Morphology Posterior Estimation Network (GaMPEN) to estimate morphological parameters and associated uncertainties for million galaxies in the Hyper Supr…
A Framework for Obtaining Accurate Posteriors of Strong Gravitational Lensing Parameters with Flexible Priors and Implicit Likelihoods using Density Estimation
Ronan Legin, Yashar Hezaveh, Laurence Perreault-Levasseur +1
We report the application of implicit likelihood inference to the prediction of the macro-parameters of strong lensing systems with neural networks. This allows us to perform deep…
Disks, spikes, and clouds: distinguishing environmental effects on BBH gravitational waveforms
Philippa S. Cole, Gianfranco Bertone, Adam Coogan +5
Future gravitational wave interferometers such as LISA, Taiji, DECIGO, and TianQin, will enable precision studies of the environment surrounding black holes. In this paper, we stud…
Building a Subspace of Policies for Scalable Continual Learning
Jean-Baptiste Gaya, Thang Doan, Lucas Caccia +3
The ability to continuously acquire new knowledge and skills is crucial for autonomous agents. Existing methods are typically based on either fixed-size models that struggle to lea…
: Mock Challenge for a Forward Modeling Approach to Galaxy Clustering
ChangHoon Hahn, Michael Eickenberg, Shirley Ho +7
Simulation-Based Inference of Galaxies () is a forward modeling framework for analyzing galaxy clustering using simulation-based inference. In this work…
The impact of weak lensing on Type Ia supernovae luminosity distances
Paul Shah, Pablo Lemos, Ofer Lahav
When Type Ia supernovae are used to infer cosmological parameters, their luminosities are compared to those from a homogeneous cosmology. In this note we propose a test to examine…
One never walks alone: the effect of the perturber population on subhalo measurements in strong gravitational lenses
Adam Coogan, Noemi Anau Montel, Konstantin Karchev +3
Analyses of extended arcs in strong gravitational lensing images to date have constrained the properties of dark matter by measuring the parameters of one or two individual subhalo…
Dynamical Origin for the Collinder 132-Gulliver 21 Stream: A Mixture of three Co-Moving Populations with an Age Difference of 250 Myr
Xiaoying Pang, Yuqian Li, Shih-Yun Tang +6
We use Gaia DR3 data to study the Collinder 132-Gulliver 21 region via the machine learning algorithm StarGO, and find eight subgroups of stars (ASCC 32, Collinder 132 gp 1--6, Gul…
Measuring dark matter spikes around primordial black holes with Einstein Telescope and Cosmic Explorer
Philippa S. Cole, Adam Coogan, Bradley J. Kavanagh +1
Future ground-based gravitational wave observatories will be ideal probes of the environments surrounding black holes with masses . Binary black hole merg…
DiverGet: A Search-Based Software Testing Approach for Deep Neural Network Quantization Assessment
Ahmed Haj Yahmed, Houssem Ben Braiek, Foutse Khomh +2
Quantization is one of the most applied Deep Neural Network (DNN) compression strategies, when deploying a trained DNN model on an embedded system or a cell phone. This is owing to…
GaMPEN: A Machine Learning Framework for Estimating Bayesian Posteriors of Galaxy Morphological Parameters
Aritra Ghosh, C. Megan Urry, Amrit Rau +11
We introduce a novel machine learning framework for estimating the Bayesian posteriors of morphological parameters for arbitrarily large numbers of galaxies. The Galaxy Morphology…
Hazma Meets HERWIG4DM: Precision Gamma-Ray, Neutrino, and Positron Spectra for Light Dark Matter
Adam Coogan, Logan Morrison, Tilman Plehn +2
We present a new open-source package, Hazma 2, that computes accurate spectra relevant for indirect dark matter searches for photon, neutrino, and positron production from vector-m…
Adaptation, Comparison and Practical Implementation of Fairness Schemes in Kidney Exchange Programs
William St-Arnaud, Margarida Carvalho, Golnoosh Farnadi
In Kidney Exchange Programs (KEPs), each participating patient is registered together with an incompatible donor. Donors without an incompatible patient can also register. Then, KE…
Metrics reloaded: Recommendations for image analysis validation
Lena Maier-Hein, Annika Reinke, Patrick Godau +71
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen…
Correlated Read Noise Reduction in Infrared Arrays Using Deep Learning
Guillaume Payeur, Étienne Artigau, Laurence Perreault-Levasseur +1
We present a new procedure rooted in deep learning to construct science images from data cubes collected by astronomical instruments using HxRG detectors in low-flux regimes. It im…
Estimating the warm dark matter mass from strong lensing images with truncated marginal neural ratio estimation
Noemi Anau Montel, Adam Coogan, Camila Correa +2
Precision analysis of galaxy-galaxy strong gravitational lensing images provides a unique way of characterizing small-scale dark matter halos, and could allow us to uncover the fun…
Self-Supervised Anomaly Detection in Computer Vision and Beyond: A Survey and Outlook
Hadi Hojjati, Thi Kieu Khanh Ho, Narges Armanfard
Anomaly detection (AD) plays a crucial role in various domains, including cybersecurity, finance, and healthcare, by identifying patterns or events that deviate from normal behavio…
Galaxies and Halos on Graph Neural Networks: Deep Generative Modeling Scalar and Vector Quantities for Intrinsic Alignment
Yesukhei Jagvaral, François Lanusse, Sukhdeep Singh +3
In order to prepare for the upcoming wide-field cosmological surveys, large simulations of the Universe with realistic galaxy populations are required. In particular, the tendency…
Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated Learning
Georg Pichler, Marco Romanelli, Leonardo Rey Vega +1
Federated Learning is expected to provide strong privacy guarantees, as only gradients or model parameters but no plain text training data is ever exchanged either between the clie…
UnShadowNet: Illumination Critic Guided Contrastive Learning For Shadow Removal
Subhrajyoti Dasgupta, Arindam Das, Senthil Yogamani +4
Shadows are frequently encountered natural phenomena that significantly hinder the performance of computer vision perception systems in practical settings, e.g., autonomous driving…
Subgraph Retrieval Enhanced Model for Multi-hop Knowledge Base Question Answering
Jing Zhang, Xiaokang Zhang, Jifan Yu +4
Recent works on knowledge base question answering (KBQA) retrieve subgraphs for easier reasoning. A desired subgraph is crucial as a small one may exclude the answer but a large on…
Efficient Gravitational Wave Template Bank Generation with Differentiable Waveforms
Adam Coogan, Thomas D. P. Edwards, Horng Sheng Chia +6
The most sensitive search pipelines for gravitational waves from compact binary mergers use matched filters to extract signals from the noisy data stream coming from gravitational…