Laurence Perreault Levasseur

According to our database, Laurence Perreault Levasseur authored at least 12 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Tackling the Problem of Distributional Shifts: Correcting Misspecified, High-Dimensional Data-Driven Priors for Inverse Problems.

Gabriel Missael Barco, Alexandre Adam, Connor Stone, Yashar Hezaveh, Laurence Perreault Levasseur

CoRR, 2024

PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation.

Pablo Lemos, Sammy Sharief, Nikolay Malkin, Laurence Perreault Levasseur, Yashar Hezaveh

CoRR, 2024

Improving Gradient-Guided Nested Sampling for Posterior Inference.

Pablo Lemos, Nikolay Malkin, Will Handley, Yoshua Bengio, Yashar Hezaveh, Laurence Perreault Levasseur

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Bayesian Imaging for Radio Interferometry with Score-Based Priors.

Noe Dia, M. J. Yantovski-Barth, Alexandre Adam, Micah Bowles, Pablo Lemos, Anna M. M. Scaife, Yashar Hezaveh, Laurence Perreault Levasseur

CoRR, 2023

Echoes in the Noise: Posterior Samples of Faint Galaxy Surface Brightness Profiles with Score-Based Likelihoods and Priors.

Alexandre Adam, Connor Stone, Connor Bottrell, Ronan Legin, Yashar Hezaveh, Laurence Perreault Levasseur

CoRR, 2023

Pixelated Reconstruction of Foreground Density and Background Surface Brightness in Gravitational Lensing Systems using Recurrent Inference Machines.

Alexandre Adam, Laurence Perreault Levasseur, Yashar Hezaveh, Max Welling

CoRR, 2023

Lie Point Symmetry and Physics-Informed Networks.

Tara Akhound-Sadegh, Laurence Perreault Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Sampling-Based Accuracy Testing of Posterior Estimators for General Inference.

Pablo Lemos, Adam Coogan, Yashar Hezaveh, Laurence Perreault Levasseur

Proceedings of the International Conference on Machine Learning, 2023

2022

Posterior samples of source galaxies in strong gravitational lenses with score-based priors.

Alexandre Adam, Adam Coogan, Nikolay Malkin, Ronan Legin, Laurence Perreault Levasseur, Yashar Hezaveh, Yoshua Bengio

CoRR, 2022

2020

deep21: a Deep Learning Method for 21cm Foreground Removal.

T. Lucas Makinen, Lachlan Lancaster, Francisco Villaescusa-Navarro, Peter Melchior, Shirley Ho, Laurence Perreault Levasseur, David N. Spergel

CoRR, 2020

Bayesian Neural Networks.

Tom Charnock, Laurence Perreault Levasseur, François Lanusse

CoRR, 2020

2019

HIGAN: Cosmic Neutral Hydrogen with Generative Adversarial Networks.

Juan Zamudio-Fernandez, Atakan Okan, Francisco Villaescusa-Navarro, Seda Bilaloglu, Asena Derin Cengiz, Siyu He, Laurence Perreault Levasseur, Shirley Ho

CoRR, 2019