Laurence Perreault Levasseur

22 papers A* 4Journal 18
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Fast Generative Framework for High-dimensional Posterior Sampling: Application to CMB Delensing.
CoRR
Hadi Sotoudeh, Pablo Lemos, Laurence Perreault Levasseur
2026 J jnl
Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration.
CoRR
LSST Dark Energy Science Collaboration, Eric Aubourg, Camille Avestruz, Matthew R. Becker, Biswajit Biswas, Rahul Biswas, Boris Bolliet, Adam S. Bolton, Clecio R. Bom, Raphaël Bonnet-Guerrini, Alexandre Boucaud, Jean-Eric Campagne, Chihway Chang, Aleksandra Ciprijanovic, Johann Cohen-Tanugi, Michael W. Coughlin, John Franklin Crenshaw, Juan C. Cuevas-Tello, Juan de Vicente, Seth W. Digel, Steven Dillmann, Mariano Javier de León Dominguez Romero, Alex Drlica-Wagner, Sydney Erickson, Alexander T. Gagliano, Christos Georgiou, Aritra Ghosh, Matthew Grayling, Kirill A. Grishin, Alan Heavens, Lindsay R. House, Mustapha Ishak, Wassim Kabalan, Arun Kannawadi, François Lanusse, C. Danielle Leonard, Pierre-François Léget, Michelle Lochner, Yao-Yuan Mao, Peter Melchior, Grant Merz, Martin Millon, Anais Möller, Gautham Narayan, Yuuki Omori, Hiranya Peiris, Laurence Perreault Levasseur, Andrés Alejandro Plazas Malagón, Nesar Ramachandra, Benjamin Remy, Cécile Roucelle, Jaime Ruiz-Zapatero, Stefan Schuldt, Ignacio Sevilla-Noarbe, Ved G. Shah, Tjitske Starkenburg, Stephen Thorp, Laura Toribio San Cipriano, Tilman Tröster, Roberto Trotta, Padma Venkatraman, Amanda Wasserman, Tim White, Justine Zeghal, Tianqing Zhang, Yuanyuan Zhang
2025 J jnl
Blind Strong Gravitational Lensing Inversion: Joint Inference of Source and Lens Mass with Score-Based Models.
CoRR
Gabriel Missael Barco, Ronan Legin, Connor Stone, Yashar Hezaveh, Laurence Perreault Levasseur
2025 J jnl
IRIS: A Bayesian Approach for Image Reconstruction in Radio Interferometry with expressive Score-Based priors.
CoRR
Noe Dia, M. J. Yantovski-Barth, Alexandre Adam, Micah Bowles, Laurence Perreault Levasseur, Yashar Hezaveh, Anna M. M. Scaife
2025 A* conf
PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation.
ICLR
Pablo Lemos, Sammy Nasser Sharief, Nikolay Malkin, Salma Salhi, Connor Stone, Laurence Perreault Levasseur, Yashar Hezaveh
2025 J jnl
Solving Bayesian inverse problems with diffusion priors and off-policy RL.
CoRR
Luca Scimeca, Siddarth Venkatraman, Moksh Jain, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yashar Hezaveh, Laurence Perreault Levasseur, Yoshua Bengio, Glen Berseth, Nikolay Malkin
2024 J jnl
Caustics: A Python Package for Accelerated Strong Gravitational Lensing Simulations.
J. Open Source Softw.
Connor Stone, Alexandre Adam, Adam Coogan, M. J. Yantovski-Barth, Andreas Filipp, Landung Setiawan, Cordero Core, Ronan Legin, Charles Wilson, Gabriel Missael Barco, Yashar Hezaveh, Laurence Perreault Levasseur
2024 A* conf
Improving Gradient-Guided Nested Sampling for Posterior Inference.
ICML
Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault Levasseur
2024 J jnl
PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation.
CoRR
Pablo Lemos, Sammy Sharief, Nikolay Malkin, Laurence Perreault Levasseur, Yashar Hezaveh
2024 J jnl
Tackling the Problem of Distributional Shifts: Correcting Misspecified, High-Dimensional Data-Driven Priors for Inverse Problems.
CoRR
Gabriel Missael Barco, Alexandre Adam, Connor Stone, Yashar Hezaveh, Laurence Perreault Levasseur
2023 J jnl
Bayesian Imaging for Radio Interferometry with Score-Based Priors.
CoRR
Noe Dia, M. J. Yantovski-Barth, Alexandre Adam, Micah Bowles, Pablo Lemos, Anna M. M. Scaife, Yashar Hezaveh, Laurence Perreault Levasseur
2023 J jnl
Echoes in the Noise: Posterior Samples of Faint Galaxy Surface Brightness Profiles with Score-Based Likelihoods and Priors.
CoRR
Alexandre Adam, Connor Stone, Connor Bottrell, Ronan Legin, Yashar Hezaveh, Laurence Perreault Levasseur
2023 J jnl
Improving Gradient-guided Nested Sampling for Posterior Inference.
CoRR
Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault Levasseur
2023 J jnl
Lie Point Symmetry and Physics Informed Networks.
CoRR
Tara Akhound-Sadegh, Laurence Perreault Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh
2023 A* conf
Lie Point Symmetry and Physics-Informed Networks.
NeurIPS
Tara Akhound-Sadegh, Laurence Perreault Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh
2023 J jnl
Pixelated Reconstruction of Foreground Density and Background Surface Brightness in Gravitational Lensing Systems using Recurrent Inference Machines.
CoRR
Alexandre Adam, Laurence Perreault Levasseur, Yashar Hezaveh, Max Welling
2023 A* conf
Sampling-Based Accuracy Testing of Posterior Estimators for General Inference.
ICML
Pablo Lemos, Adam Coogan, Yashar Hezaveh, Laurence Perreault Levasseur
2023 J jnl
Sampling-Based Accuracy Testing of Posterior Estimators for General Inference.
CoRR
Pablo Lemos, Adam Coogan, Yashar Hezaveh, Laurence Perreault Levasseur
2022 J jnl
Posterior samples of source galaxies in strong gravitational lenses with score-based priors.
CoRR
Alexandre Adam, Adam Coogan, Nikolay Malkin, Ronan Legin, Laurence Perreault Levasseur, Yashar Hezaveh, Yoshua Bengio
2020 J jnl
Bayesian Neural Networks.
CoRR
Tom Charnock, Laurence Perreault Levasseur, François Lanusse
2020 J jnl
deep21: a Deep Learning Method for 21cm Foreground Removal.
CoRR
T. Lucas Makinen, Lachlan Lancaster, Francisco Villaescusa-Navarro, Peter Melchior, Shirley Ho, Laurence Perreault Levasseur, David N. Spergel
2019 J jnl
HIGAN: Cosmic Neutral Hydrogen with Generative Adversarial Networks.
CoRR
Juan Zamudio-Fernandez, Atakan Okan, Francisco Villaescusa-Navarro, Seda Bilaloglu, Asena Derin Cengiz, Siyu He, Laurence Perreault Levasseur, Shirley Ho